Sabina Tangaro

Scopus Publications

From networks of data to networks of care in clinical medicine: this is not artificial intelligence
Pierfrancesco Novielli, Roberto Bellotti, Mohamad Khalil, Piero Portincasa, Sabina Tangaro
European Journal of Internal Medicine, 2026
Explainable AI-Based Hyperspectral Classification Reveals Differences in Spectral Response over Phenological Stages
Rameez Ahsen, Pierpaolo Di Bitonto, Pierfrancesco Novielli, Michele Magarelli, Donato Romano, et al.
Biology, 2026
Optimizing nitrogen (N) fertilization is essential for sustaining durum wheat yield and grain quality while reducing the environmental impacts associated with N over-application. Hyperspectral sensing provides a rapid and non-destructive approach for monitoring crop N status. However, high-dimensional data, phenology-dependent spectral responses, and spatial autocorrelation in field measurements limit robust nitrogen classification and interpretation. This study evaluated hyperspectral-based nitrogen status classification in durum wheat under Mediterranean field conditions and identified key spectral regions using explainable artificial intelligence. A field experiment was conducted in Southern Italy using ten N fertilization rates (0–180 kg N ha−1). Canopy reflectance was acquired at the booting and heading stages from georeferenced sampling locations. Three nitrogen stratification strategies (binary Low–High, Extreme, and three-level) were evaluated using Random Forest, SVM-RBF, and XGBoost classifiers. Model performance was assessed using spatially independent Leave-One-Plot-Out cross-validation at both the sample and plot levels, with plot-level predictions derived through majority voting. Classification robustness was strongly influenced by the stratification strategy and phenological stage. The binary Low–High stratification achieved the highest sample-level accuracy, with a maximum of 0.78 at booting (SVM-RBF) and 0.75 at heading (SVM-RBF), whereas the Extreme stratification produced intermediate performance, with maximum accuracies of 0.73 at booting (SVM-RBF) and 0.63 at heading (XGBoost). Plot-level aggregation improved performance, reaching up to 0.90 at booting and 1.00 at heading. SHAP analysis highlighted red, red-edge, and near-infrared wavelengths as the dominant contributors, with increased reliance on longer wavelengths at the heading. Overall, explainable machine learning provides a robust framework for hyperspectral nitrogen monitoring in durum wheat.
High-Resolution NO2, O3, and PMs Estimation in Puglia: Leveraging AI and Explainability Techniques
Alessandro Fania, Giovanni Lorusso, Roberto Cilli, Nicola Amoroso, Maria Adamo, et al.
Atmosphere, 2026
Air pollution remains a major environmental challenge, with severe impacts on human health and ecosystems. Recent advances in satellite technology have transformed air quality monitoring by enabling global, continuous observations of atmospheric pollutants. However, satellite data often lack the precision of ground-based stations. This study aims to develop a machine learning model to predict daily surface concentrations of key air pollutants (NO2, O3, PM10, and PM2.5) at high spatial resolution (300 m) in the Apulia region. Using Regional Environmental Protection Agency (ARPA) station data from 2019 to 2022 and meteorological, geographic, land-use, and temporal variables, we trained an XGBoost model on a 300 m grid. Model performance, assessed by repeated cross-validation, showed an average R2 of 0.71, with values of 0.77 for NO2, 0.78 for O3, 0.67 for PM2.5, and 0.64 for PM10. eXplainable AI (XAI) methods confirmed strong alignment with established scientific knowledge, enhancing model reliability and offering insights into pollutant distribution drivers.
Deep Learning for Tomato Ripeness Detection: A YOLO-Based Approach
Rameez Ahsen, Pierpaolo Di Bitonto, Michele Magarelli, Donato Romano, Pierfrancesco Novielli, et al.
Lecture Notes in Computer Science, 2026
Exponential random graph-based eXplainable Artificial Intelligence for Alzheimer disease
Nicola Amoroso, Ester Pantaleo, Marianna La Rocca, Loredana Bellantuono, Saverio Pascazio, et al.
Physical Review E, 2026
The use of statistical physics models to investigate real-world networks and reveal their underlying dynamics has shown promising results and acquired increasing attention. Here, we show how exponential random-graph (ERG) models can be suitably adopted to characterize how Alzheimer's disease (AD) affects brain connectivity. Magnetic-resonance imaging (MRI) of the brain was used to define a brain connectivity network whose nodes are the different brain regions, and the links indicate the pairwise structural relationships. Based on T1-weighted MRI brain scans of 126 normal controls (NC) and 92 AD patients, ERGs were able to outline both “global” and “local” disease patterns. Our findings demonstrate that ERGs accurately highlight how AD affects brain connectivity reaching an overall classification accuracy of 0.82 ± 0.08 . Besides, ERGs outline which regions of the brain are the most affected by the disease, thus proving to be a formidable instrument also to investigate the disease pathological mechanisms; more importantly, as these effects are evaluated at patient level, they can be exploited to design innovative diagnosis support systems or to provide a novel explainable framework for decision support systems. Finally, thanks to its generality, the approach proposed in this study paves the way for further applications and investigations inquiring into the use of ERGs for other diseases and different data sources or the use of alternative models.
Unlocking extra virgin olive oil identification: predicting ethyl esters with explainable AI on IR spectra
Michele Magarelli, Silvia Grassi, Giacomo Squeo, Pierfrancesco Novielli, Roberto Bellotti, et al.
Food Chemistry, 2026
Hyperspectral Imaging and Machine Learning for Geographic Discrimination of Wheat Flours
Michele Magarelli, Florinda Artuso, Pierfrancesco Novielli, Alessandra Pasquo, Donato Romano, et al.
Lecture Notes in Computer Science, 2026
Personalized colorectal cancer risk assessment through explainable AI and Gut microbiome profiling
Pierfrancesco Novielli, Simone Baldi, Donato Romano, Michele Magarelli, Domenico Diacono, et al.
Gut Microbes, 2025
Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research
Jonathan L. Golob, Tomiko T. Oskotsky, Alice S. Tang, Alennie Roldan, Verena Chung, et al.
Cell Reports Medicine, 2025
Leveraging Explainable Artificial Intelligence for Genotype-to-Phenotype Prediction: A Case Study in Arabidopsis thaliana
Pierfrancesco Novielli, Nelson Nazzicari, Stefano Pavan, Chiara Delvento, Domenico Diacono, et al.
Applied System Innovation, 2025
Predicting phenotypes from genomic data can significantly advance agriculture. Genomic selection, which uses genome-wide DNA markers to identify individuals with high genetic value, enhances the accuracy of breeding programs. While linear models are routinely used for genomic selection (GS), machine learning (ML) models offer complementary potential. In this study, robust ML-based models were developed to predict five phenotypic traits—three related to flowering time and two to leaf number—in Arabidopsis thaliana, a model plant with a fully sequenced genome. Using explainable artificial intelligence (XAI), specifically SHapley Additive exPlanations (SHAP) values, we identified SNPs that contributed most to trait prediction. Many of these SNPs were located in or near genes known to regulate flowering and stem elongation, such as DOG1 and VIN3, supporting the biological plausibility of the model. SHAP also enabled local interpretability at the single-plant level, revealing the genotypic basis of individual predictions. Our results indicate that integrating ML with XAI improves model interpretability and provides predictive performance comparable to traditional methods. This approach confirms known genotype–phenotype relationships and highlights new candidate loci, paving the way for functional validation. The proposed methodology offers promising applications in precision breeding and translation of insights from Arabidopsis to crop species.
Leveraging explainable AI to predict soil respiration sensitivity and its drivers for climate change mitigation
Pierfrancesco Novielli, Michele Magarelli, Donato Romano, Pierpaolo Di Bitonto, Anna Maria Stellacci, et al.
Scientific Reports, 2025
Automated olive grove classification and tree counting in very high resolution aerial imagery using deep learning
Ester Pantaleo, Vincenzo Giannico, Roberto Cilli, Salvatore Camposeo, Mario Elia, et al.
Smart Agricultural Technology, 2025
A joint complex network and machine learning approach for the identification of discriminative gene communities in autistic brain
Antonio Lacalamita, Ester Pantaleo, Alfonso Monaco, Loredana Bellantuono, Alessandro Fania, et al.
Plos One, 2025
Unveiling complex patterns: An information-theoretic approach to high-order behaviors in microarray data
Antonio Lacalamita, Alfonso Monaco, Grazia Serino, Daniele Marinazzo, Nicola Amoroso, et al.
Plos One, 2025
Transfer Entropy and O-Information to Detect Grokking in Tensor Network Multi-Class Classification Problems
Domenico Pomarico, Roberto Cilli, Alfonso Monaco, Loredana Bellantuono, Marianna La Rocca, et al.
Technologies, 2025
Data-driven assessment of Apulian road network resilience: Bridge unavailability and inner municipality isolation impact
Niloofar Kheirkhahan, Loredana Bellantuono, Nicola Amoroso, Roberto Cilli, Lorenzo De Biase, et al.
Plos One, 2025
An Italian Patent Multi-Label Classification System to Support the Innovation Demand and Supply Matching
Nicola Amoroso, Annamaria Demarinis Loiotile, Ester Pantaleo, Giuseppe Conti, Shiva Loccisano, et al.
Sustainability Switzerland, 2025
Vertical Dense Jets in Crossflows: A Preliminary Study with Lattice Boltzmann Methods
Maria Grazia Giordano, Jérôme Jacob, Piergiorgio Fusco, Sabina Tangaro, Daniela Malcangio
Fluids, 2025
Network assortativity for a multidimensional evaluation of socio-economic territorial biases in university rankings
Loredana Bellantuono, Andrea Lo Sasso, Nicola Amoroso, Alfonso Monaco, Sabina Tangaro, et al.
Plos One, 2025
Predictive and Explainable Machine Learning Models for Endocrine, Nutritional, and Metabolic Mortality in Italy Using Geolocalized Pollution Data
Donato Romano, Michele Magarelli, Pierfrancesco Novielli, Domenico Diacono, Pierpaolo Di Bitonto, et al.
Applied System Innovation, 2025
Harnessing Digital Twins for Sustainable Agricultural Water Management: A Systematic Review
Rameez Ahsen, Pierpaolo Di Bitonto, Pierfrancesco Novielli, Michele Magarelli, Donato Romano, et al.
Applied Sciences Switzerland, 2025
Emerging generalization advantage of quantum-inspired machine learning in the diagnosis of hepatocellular carcinoma
Domenico Pomarico, Alfonso Monaco, Nicola Amoroso, Loredana Bellantuono, Antonio Lacalamita, et al.
Discover Applied Sciences, 2025
Measuring water pollution effects on antimicrobial resistance through explainable artificial intelligence
Alfonso Monaco, Mario Caruso, Loredana Bellantuono, Roberto Cazzolla Gatti, Alessandro Fania, et al.
Environmental Pollution, 2025
Bridging Structural and Functional Imaging: Integrated PET/CT Radiomics with Explainable Machine Learning
Ceur Workshop Proceedings, 2025
Explainable artificial intelligence advances breath analysis for monitoring Crohn’s disease
Nuovo Cimento Della Societa Italiana Di Fisica C, 2025
Time Sensitive and Oversampling Learning for Systemic Crisis Forecasting
Francesco De Nicolò, Marianna La Rocca, Antonio Marrone, Alfonso Monaco, Sabina Tangaro, et al.
New Economic Windows, 2025
Data-Driven Innovations in Food Safety: The Role of AI and Big Data in METROFOOD-IT
Michele Magarelli, Pierpaolo Di Bitonto, Donato Romano, Pierfrancesco Novielli, Rameez Ahsen, et al.
2025 IEEE International Workshop on Metrology for Industry 4 0 and Iot Metroind4 0 and Iot 2025 Proceedings, 2025
Prediction of Winter Wheat Parameters with Planet SuperDove Imagery and Explainable Artificial Intelligence
Gabriele De Carolis, Vincenzo Giannico, Leonardo Costanza, Francesca Ardito, Anna Maria Stellacci, et al.
Agronomy, 2025
Machine learning and XAI approaches highlight the strong connection between O3 and NO2 pollutants and Alzheimer’s disease
Alessandro Fania, Alfonso Monaco, Nicola Amoroso, Loredana Bellantuono, Roberto Cazzolla Gatti, et al.
Scientific Reports, 2024
Robust machine learning challenge: An AIFM multicentric competition to spread knowledge, identify common pitfalls and recommend best practice
Michele Maddalo, Annarita Fanizzi, Nicola Lambri, Emiliano Loi, Marco Branchini, et al.
Physica Medica, 2024
Personalized identification of autism-related bacteria in the gut microbiome using explainable artificial intelligence
Pierfrancesco Novielli, Donato Romano, Michele Magarelli, Domenico Diacono, Alfonso Monaco, et al.
Iscience, 2024
Climate Change and Soil Health: Explainable Artificial Intelligence Reveals Microbiome Response to Warming
Pierfrancesco Novielli, Michele Magarelli, Donato Romano, Lorenzo de Trizio, Pierpaolo Di Bitonto, et al.
Machine Learning and Knowledge Extraction, 2024
Developing an ensemble machine learning study: Insights from a multi-center proof-of-concept study
Annarita Fanizzi, Federico Fadda, Michele Maddalo, Sara Saponaro, Leda Lorenzon, et al.
Plos One, 2024
Tackling the small data problem in medical image classification with artificial intelligence: a systematic review
Stefano Piffer, Leonardo Ubaldi, Sabina Tangaro, Alessandra Retico, Cinzia Talamonti
Progress in Biomedical Engineering, 2024
Insights from Explainable Artificial Intelligence of Pollution and Socioeconomic Influences for Respiratory Cancer Mortality in Italy
Donato Romano, Pierfrancesco Novielli, Domenico Diacono, Roberto Cilli, Ester Pantaleo, et al.
Journal of Personalized Medicine, 2024
Estimation of Daily Ground Level Air Pollution in Italian Municipalities with Machine Learning Models Using Sentinel-5P and ERA5 Data
Alessandro Fania, Alfonso Monaco, Ester Pantaleo, Tommaso Maggipinto, Loredana Bellantuono, et al.
Remote Sensing, 2024
Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research
Jonathan L. Golob, Tomiko T. Oskotsky, Alice S. Tang, Alennie Roldan, Verena Chung, et al.
Cell Reports Medicine, 2024
Air pollution and mortality for cancer of the respiratory system in Italy: an explainable artificial intelligence approach
Donato Romano, Pierfrancesco Novielli, Roberto Cilli, Nicola Amoroso, Alfonso Monaco, et al.
Frontiers in Public Health, 2024
Securing origin integrity through Machine Learning analysis of Mozzarella di Bufala PDO Microbiome
Michele Magarelli, Pierpaolo Di Bitonto, Francesca De Filippis, Pierfrancesco Novielli, Raffaele Magliulo, et al.
2024 IEEE International Workshop on Metrology for Industry 4 0 and Iot Metroind4 0 and Iot 2024 Proceedings, 2024
Explainable artificial intelligence and microbiome data for food geographical origin: the Mozzarella di Bufala Campana PDO Case of Study
Michele Magarelli, Pierfrancesco Novielli, Francesca De Filippis, Raffaele Magliulo, Pierpaolo Di Bitonto, et al.
Frontiers in Microbiology, 2024
Explainable artificial intelligence for genotype-to-phenotype prediction in plant breeding: a case study with a dataset from an almond germplasm collection
Pierfrancesco Novielli, Donato Romano, Stefano Pavan, Pasquale Losciale, Anna Maria Stellacci, et al.
Frontiers in Plant Science, 2024
METROFOOD-IT: A data platform proposal using Agrifood Smart Data Model
Pierpaolo Di Bitonto, Lorenzo De Trizio, Michele Magarelli, Domenico Diacono, Pierfrancesco Novielli, et al.
2024 IEEE International Workshop on Metrology for Industry 4 0 and Iot Metroind4 0 and Iot 2024 Proceedings, 2024
Precision Agriculture: Integrating Sensors for Weed Detection using Machine Learning in Agriculture Fields
Rameez Ahsen, Pierpaolo Di Bitonto, Lorenzo De Trizio, Michele Magarelli, Donato Romano, et al.
2024 7th IEEE International Humanitarian Technologies Conference Ihtc 2024, 2024
Innovative Virtual Reality Based Training in the Agri-Food Sector: Insights from METROFOOD-IT
Pierpaolo Di Bitonto, Lorenzo De Trizio, Michele Magarelli, Donato Romano, Pierfrancesco Novielli, et al.
2024 7th IEEE International Humanitarian Technologies Conference Ihtc 2024, 2024
From data to nutrition: the impact of computing infrastructure and artificial intelligence
Pierpaolo Di Bitonto, Michele Magarelli, Pierfrancesco Novielli, Donato Romano, Domenico Diacono, et al.
Exploration of Foods and Foodomics, 2024
Explainable artificial intelligence for microbiome data analysis in colorectal cancer biomarker identification
Pierfrancesco Novielli, Donato Romano, Michele Magarelli, Pierpaolo Di Bitonto, Domenico Diacono, et al.
Frontiers in Microbiology, 2024
Unraveling the microbiome-metabolome nexus: a comprehensive study protocol for personalized management of Behçet’s disease using explainable artificial intelligence
Sabina Tangaro, Giuseppe Lopalco, Daniele Sabella, Vincenzo Venerito, Pierfrancesco Novielli, et al.
Frontiers in Microbiology, 2024
Deep learning approach for denoising low-SNR correlation plenoptic images
Francesco Scattarella, Domenico Diacono, Alfonso Monaco, Nicola Amoroso, Loredana Bellantuono, et al.
Scientific Reports, 2023
A Dementia mortality rates dataset in Italy (2012–2019)
Alessandro Fania, Alfonso Monaco, Nicola Amoroso, Loredana Bellantuono, Roberto Cazzolla Gatti, et al.
Scientific Data, 2023
An eXplainable Artificial Intelligence analysis of Raman spectra for thyroid cancer diagnosis
Loredana Bellantuono, Raffaele Tommasi, Ester Pantaleo, Martina Verri, Nicola Amoroso, et al.
Scientific Reports, 2023
Artificial Intelligence and Complex Network Approaches Reveal Potential Gene Biomarkers for Hepatocellular Carcinoma
Antonio Lacalamita, Grazia Serino, Ester Pantaleo, Alfonso Monaco, Nicola Amoroso, et al.
International Journal of Molecular Sciences, 2023
PSI Spatially Constrained Clustering: The Sibari and Metaponto Coastal Plains
Nicola Amoroso, Roberto Cilli, Davide Oscar Nitti, Raffaele Nutricato, Muzaffer Can Iban, et al.
Remote Sensing, 2023
An eXplainability Artificial Intelligence approach to brain connectivity in Alzheimer's disease
Nicola Amoroso, Silvano Quarto, Marianna La Rocca, Sabina Tangaro, Alfonso Monaco, et al.
Frontiers in Aging Neuroscience, 2023
Innovations and Emerging Technologies: A Study of the Italian Intellectual Property Knowledge Database
Annamaria Demarinis Loiotile, Francesco De Nicolò, Alfonso Monaco, Sabina Tangaro, Shiva Loccisano, et al.
International Conference on Agents and Artificial Intelligence, 2023
The verbalization of numbers: An explainable framework for tourism online reviews
Francesco De Nicolò, Loredana Bellantuono, Dario Borzì, Matteo Bregonzio, Roberto Cilli, et al.
International Journal of Engineering Business Management, 2023
Machine learning approaches in microbiome research: challenges and best practices
Georgios Papoutsoglou, Sonia Tarazona, Marta B. Lopes, Thomas Klammsteiner, Eliana Ibrahimi, et al.
Frontiers in Microbiology, 2023
Worldwide impact of lifestyle predictors of dementia prevalence: An eXplainable Artificial Intelligence analysis
Loredana Bellantuono, Alfonso Monaco, Nicola Amoroso, Antonio Lacalamita, Ester Pantaleo, et al.
Frontiers in Big Data, 2022
Sustainable development goals: conceptualization, communication and achievement synergies in a complex network framework
Loredana Bellantuono, Alfonso Monaco, Nicola Amoroso, Vincenzo Aquaro, Angela Lombardi, et al.
Applied Network Science, 2022
Territorial bias in university rankings: a complex network approach
Loredana Bellantuono, Alfonso Monaco, Nicola Amoroso, Vincenzo Aquaro, Marco Bardoscia, et al.
Scientific Reports, 2022
A robust framework to investigate the reliability and stability of explainable artificial intelligence markers of Mild Cognitive Impairment and Alzheimer’s Disease
Angela Lombardi, Domenico Diacono, Nicola Amoroso, Przemysław Biecek, Alfonso Monaco, et al.
Brain Informatics, 2022
Explainable artificial intelligence (XAI) detects wildfire occurrence in the Mediterranean countries of Southern Europe
Roberto Cilli, Mario Elia, Marina D’Este, Vincenzo Giannico, Nicola Amoroso, et al.
Scientific Reports, 2022
Best Practices in Knowledge Transfer: Insights from Top Universities
Annamaria Demarinis Loiotile, Francesco De Nicolò, Adriana Agrimi, Loredana Bellantuono, Marianna La Rocca, et al.
Sustainability Switzerland, 2022
The impact of harmonization on radiomic features in Parkinson’s disease and healthy controls: A multicenter study
Benedetta Tafuri, Angela Lombardi, Salvatore Nigro, Daniele Urso, Alfonso Monaco, et al.
Frontiers in Neuroscience, 2022
Territorial Development as an Innovation Driver: A Complex Network Approach
Francesco De Nicolò, Alfonso Monaco, Giuseppe Ambrosio, Loredana Bellantuono, Roberto Cilli, et al.
Applied Sciences Switzerland, 2022
The Use and Utility of Machine Learning in Achieving Precision Medicine in Systemic Sclerosis: A Narrative Review
Francesco Bonomi, Silvia Peretti, Gemma Lepri, Vincenzo Venerito, Edda Russo, et al.
Journal of Personalized Medicine, 2022
Accurate Evaluation of Feature Contributions for Sentinel Lymph Node Status Classification in Breast Cancer
Angela Lombardi, Nicola Amoroso, Loredana Bellantuono, Samantha Bove, Maria Colomba Comes, et al.
Applied Sciences Switzerland, 2022
A Machine Learning Approach to Predict Remission in Patients With Psoriatic Arthritis on Treatment With Secukinumab
Vincenzo Venerito, Giuseppe Lopalco, Anna Abbruzzese, Sergio Colella, Maria Morrone, et al.
Frontiers in Immunology, 2022
A Machine Learning Approach to Parkinson’s Disease Blood Transcriptomics
Ester Pantaleo, Alfonso Monaco, Nicola Amoroso, Angela Lombardi, Loredana Bellantuono, et al.
Genes, 2022
Validity of Machine Learning in Predicting Giant Cell Arteritis Flare After Glucocorticoids Tapering
Vincenzo Venerito, Giacomo Emmi, Luca Cantarini, Pietro Leccese, Marco Fornaro, et al.
Frontiers in Immunology, 2022
Satellite data and machine learning reveal a significant correlation between NO2 and COVID-19 mortality
Nicola Amoroso, Roberto Cilli, Tommaso Maggipinto, Alfonso Monaco, Sabina Tangaro, et al.
Environmental Research, 2022
Lattice Boltzmann Methods for a Dense Vertical Jet in a Channel
Proceedings of the IAHR World Congress, 2022
Multi-site harmonization of MRI data uncovers machine-learning discrimination capability in barely separable populations: An example from the ABIDE dataset
Sara Saponaro, Alessia Giuliano, Roberto Bellotti, Angela Lombardi, Sabina Tangaro, et al.
Neuroimage Clinical, 2022
PSInSAR Monitoring of Coastal Cliffs at Torre a Mare, Apulia, Italy
Nicola Amoroso, Roberto Cilli, Daniela Iasillo, Vincenzo Massimi, Alfonso Monaco, et al.
2022 IEEE Mediterranean and Middle East Geoscience and Remote Sensing Symposium M2garss 2022 Proceedings, 2022
Editorial: Explainable Artificial Intelligence (XAI) in Systems Neuroscience
Angela Lombardi, João Manuel R. S. Tavares, Sabina Tangaro
Frontiers in Systems Neuroscience, 2021
Random forests highlight the combined effect of environmental heavy metals exposure and genetic damages for cardiovascular diseases
Alfonso Monaco, Antonio Lacalamita, Nicola Amoroso, Armando D’Orta, Andrea Del Buono, et al.
Applied Sciences Switzerland, 2021
Exploring the oral microbiome in rheumatic diseases, state of art and future prospective in personalized medicine with an ai approach
Silvia Bellando-Randone, Edda Russo, Vincenzo Venerito, Marco Matucci-Cerinic, Florenzo Iannone, et al.
Journal of Personalized Medicine, 2021
Explainable Deep Learning for Personalized Age Prediction With Brain Morphology
Angela Lombardi, Domenico Diacono, Nicola Amoroso, Alfonso Monaco, João Manuel R. S. Tavares, et al.
Frontiers in Neuroscience, 2021
Complex network modelling of origin–destination commuting flows for the COVID-19 epidemic spread analysis in Italian Lombardy Region
Angela Lombardi, Nicola Amoroso, Alfonso Monaco, Sabina Tangaro, Roberto Bellotti
Applied Sciences Switzerland, 2021
A Clinical Decision Support System for Predicting Invasive Breast Cancer Recurrence: Preliminary Results
Raffaella Massafra, Agnese Latorre, Annarita Fanizzi, Roberto Bellotti, Vittorio Didonna, et al.
Frontiers in Oncology, 2021
Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy
Michele Avanzo, Massimiliano Porzio, Leda Lorenzon, Lisa Milan, Roberto Sghedoni, et al.
Physica Medica, 2021
Brain Age Prediction With Morphological Features Using Deep Neural Networks: Results From Predictive Analytic Competition 2019
Angela Lombardi, Alfonso Monaco, Giacinto Donvito, Nicola Amoroso, Roberto Bellotti, et al.
Frontiers in Psychiatry, 2021
Predicting brain age with complex networks: From adolescence to adulthood
Loredana Bellantuono, Luca Marzano, Marianna La Rocca, Dominique Duncan, Angela Lombardi, et al.
Neuroimage, 2021
Identifying potential gene biomarkers for Parkinson's disease through an information entropy based approach
A Monaco, E Pantaleo, N Amoroso, L Bellantuono, A Lombardi, et al.
Physical Biology, 2021
A primer on machine learning techniques for genomic applications
Alfonso Monaco, Ester Pantaleo, Nicola Amoroso, Antonio Lacalamita, Claudio Lo Giudice, et al.
Computational and Structural Biotechnology Journal, 2021
Multi-time-scale features for accurate respiratory sound classification
Alfonso Monaco, Nicola Amoroso, Loredana Bellantuono, Ester Pantaleo, Sabina Tangaro, et al.
Applied Sciences Switzerland, 2020
An equity-oriented rethink of global rankings with complex networks mapping development
Loredana Bellantuono, Alfonso Monaco, Sabina Tangaro, Nicola Amoroso, Vincenzo Aquaro, et al.
Scientific Reports, 2020
Potential energy of complex networks: a quantum mechanical perspective
Nicola Amoroso, Loredana Bellantuono, Saverio Pascazio, Angela Lombardi, Alfonso Monaco, et al.
Scientific Reports, 2020
Psi clustering for the assessment of underground infrastructure deterioration
Nicola Amoroso, Roberto Cilli, Loredana Bellantuono, Vincenzo Massimi, Alfonso Monaco, et al.
Remote Sensing, 2020
Association between structural connectivity and generalized cognitive spectrum in alzheimer’s disease
Angela Lombardi, Nicola Amoroso, Domenico Diacono, Alfonso Monaco, Giancarlo Logroscino, et al.
Brain Sciences, 2020
Mapping digital governance projects through complex networks
Loredana Bellantuono, Alfonso Monaco, Nicola Amoroso, Sabina Tangaro, Vincenzo Aquaro, et al.
ACM International Conference Proceeding Series, 2020
Radiomic analysis in contrast-enhanced spectral mammography for predicting breast cancer histological outcome
Daniele La Forgia, Annarita Fanizzi, Francesco Campobasso, Roberto Bellotti, Vittorio Didonna, et al.
Diagnostics, 2020
Machine learning for cloud detection of globally distributed sentinel-2 images
Roberto Cilli, Alfonso Monaco, Nicola Amoroso, Andrea Tateo, Sabina Tangaro, et al.
Remote Sensing, 2020
Extensive evaluation of morphological statistical harmonization for brain age prediction
Angela Lombardi, Nicola Amoroso, Domenico Diacono, Alfonso Monaco, Sabina Tangaro, et al.
Brain Sciences, 2020
Individual topological analysis of synchronization-based brain connectivity
Angela Lombardi, Nicola Amoroso, Domenico Diacono, Alfonso Monaco, Sabina Tangaro, et al.
Applied Sciences Switzerland, 2020
Breath analysis for early detection of malignant pleural mesothelioma: Volatile organic compounds (VOCs) determination and possible biochemical pathways
Alessia Di Gilio, Annamaria Catino, Angela Lombardi, Jolanda Palmisani, Laura Facchini, et al.
Cancers, 2020
Elite VABB 13G: A new ultrasound-guided wireless biopsy system for breast lesions. Technical characteristics and comparison with respect to traditional core-biopsy 14-16g systems
Daniele La Forgia, Alfonso Fausto, Gianluca Gatta, Graziella Di Grezia, Angela Faggian, et al.
Diagnostics, 2020
A machine learning approach on multiscale texture analysis for breast microcalcification diagnosis
Annarita Fanizzi, Teresa M. A. Basile, Liliana Losurdo, Roberto Bellotti, Ubaldo Bottigli, et al.
BMC Bioinformatics, 2020
Machine learning and DWI brain communicability networks for Alzheimer's disease detection
Eufemia Lella, Angela Lombardi, Nicola Amoroso, Domenico Diacono, Tommaso Maggipinto, et al.
Applied Sciences Switzerland, 2020
Shannon entropy approach reveals relevant genes in Alzheimer's disease
Alfonso Monaco, Nicola Amoroso, Loredana Bellantuono, Eufemia Lella, Angela Lombardi, et al.
Plos One, 2019
Ensemble discretewavelet transform and gray-level co-occurrence matrix for microcalcification cluster classification in digital mammography
Annarita Fanizzi, Teresa Maria Basile, Liliana Losurdo, Roberto Bellotti, Ubaldo Bottigli, et al.
Applied Sciences Switzerland, 2019
Multiplex networks for early diagnosis of Alzheimer’s disease
Nicola Amoroso, Marianna La Rocca, Stefania Bruno, Tommaso Maggipinto, Alfonso Monaco, et al.
Frontiers in Aging Neuroscience, 2019
Radiomics analysis on contrast-enhanced spectral mammography images for breast cancer diagnosis: A pilot study
Liliana Losurdo, Annarita Fanizzi, Teresa Maria A. Basile, Roberto Bellotti, Ubaldo Bottigli, et al.
Entropy, 2019
Assessment of network module identification across complex diseases
The DREAM Module Identification Challenge Consortium, Sarvenaz Choobdar, Mehmet E. Ahsen, Jake Crawford, Mattia Tomasoni, et al.
Nature Methods, 2019
Microcalcification detection in full-field digital mammograms: A fully automated computer-aided system
T.M.A. Basile, A. Fanizzi, L. Losurdo, R. Bellotti, U. Bottigli, et al.
Physica Medica, 2019
Modelling cognitive loads in schizophrenia by means of new functional dynamic indexes
Angela Lombardi, Cataldo Guaragnella, Nicola Amoroso, Alfonso Monaco, Leonardo Fazio, et al.
Neuroimage, 2019
Fully automated support system for diagnosis of breast cancer in contrast-enhanced spectral mammography images
Annarita Fanizzi, Liliana Losurdo, Teresa Maria A. Basile, Roberto Bellotti, Ubaldo Bottigli, et al.
Journal of Clinical Medicine, 2019
Communicability characterization of structural DWI subcortical networks in Alzheimer's disease
Eufemia Lella, Nicola Amoroso, Domenico Diacono, Angela Lombardi, Tommaso Maggipinto, et al.
Entropy, 2019
Thalamic connectivity measured with fMRI is associated with a polygenic index predicting thalamo-prefrontal gene co-expression
Linda A. Antonucci, Pasquale Di Carlo, Roberta Passiatore, Marco Papalino, Anna Monda, et al.
Brain Structure and Function, 2019
The PERSON project: a serious brain-computer interface game for treatment in cognitive impairment
Alfonso Monaco, Gianluca Sforza, Nicola Amoroso, Marica Antonacci, Roberto Bellotti, et al.
Health and Technology, 2019
Association between miRNAs expression and cognitive performances of Pediatric Multiple Sclerosis patients: A pilot study
Maria Liguori, Nicoletta Nuzziello, Marta Simone, Nicola Amoroso, Rosa Gemma Viterbo, et al.
Brain and Behavior, 2019
Age Related topological analysis of synchronization-based functional connectivity
Angela Lombardi, Nicola Amoroso, Domenico Diacono, Eufemia Lella, Roberto Bellotti, et al.
Studies in Computational Intelligence, 2019
Multidimensional neuroimaging processing in ReCaS datacenter
Angela Lombardi, Eufemia Lella, Nicola Amoroso, Domenico Diacono, Alfonso Monaco, et al.
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2019
Cross Recurrence Quantitative Analysis of Functional Magnetic Resonance Imaging
A. Lombardi, E. Lella, D. Diacono, N. Amoroso, A. Monaco, et al.
Lecture Notes in Computational Vision and Biomechanics, 2019
Applications of PDEs inpainting to magnetic particle imaging and corneal topography
Andrea Andrisani, Rosa Maria Mininni, Francesca Mazzia, Giuseppina Settanni, Alessandro Iurino, et al.
Opuscula Mathematica, 2019
Role of the contrast-enhanced spectral mammography for the diagnosis of breast metastases from extramammary neoplasms
Journal of B U on, 2019
Deep learning and multiplex networks for accurate modeling of brain age
Nicola Amoroso, Marianna La Rocca, Loredana Bellantuono, Domenico Diacono, Annarita Fanizzi, et al.
Frontiers in Aging Neuroscience, 2019
Salient networks: a novel application to study Alzheimer disease
The Alzheimer’s Disease Neuroimaging Initiative, Nicola Amoroso, Domenico Diacono, Marianna La Rocca, Roberto Bellotti, et al.
Biomedical Engineering Online, 2018
Complex networks reveal early MRI markers of Parkinson's disease
Nicola Amoroso, Marianna La Rocca, Alfonso Monaco, Roberto Bellotti, Sabina Tangaro
Medical Image Analysis, 2018
A novel approach to brain connectivity reveals early structural changes in Alzheimer's disease
Marianna La Rocca, Nicola Amoroso, Alfonso Monaco, Roberto Bellotti, Sabina Tangaro, et al.
Physiological Measurement, 2018
Communicability disruption in Alzheimer's disease connectivity networks
Eufemia Lella, Nicola Amoroso, Angela Lombardi, Tommaso Maggipinto, Sabina Tangaro, et al.
Journal of Complex Networks, 2018
Transcriptomic context of DRD1 is associated with prefrontal activity and behavior during working memory
Leonardo Fazio, Giulio Pergola, Marco Papalino, Pasquale Di Carlo, Anna Monda, et al.
Proceedings of the National Academy of Sciences of the United States of America, 2018
Deep learning reveals Alzheimer's disease onset in MCI subjects: Results from an international challenge
Nicola Amoroso, Domenico Diacono, Annarita Fanizzi, Marianna La Rocca, Alfonso Monaco, et al.
Journal of Neuroscience Methods, 2018
Trial latencies estimation of event-related potentials in EEG by means of genetic algorithms
P Da Pelo, M De Tommaso, A Monaco, S Stramaglia, R Bellotti, et al.
Journal of Neural Engineering, 2018
Alzheimer's disease diagnosis based on the Hippocampal Unified Multi-Atlas Network (HUMAN) algorithm
The Alzheimer’s Disease Neuroimaging Initiative, Nicola Amoroso, Marianna La Rocca, Roberto Bellotti, Annarita Fanizzi, et al.
Biomedical Engineering Online, 2018
Identification of “Die Hard” nodes in complex networks: A resilience approach
Angela Lombardi, Sabina Tangaro, Roberto Bellotti, Angelo Cardellicchio, Cataldo Guaragnella
Communications in Computer and Information Science, 2018
A complex network approach reveals a pivotal substructure of genes linked to schizophrenia
Alfonso Monaco, Anna Monda, Nicola Amoroso, Alessandro Bertolino, Giuseppe Blasi, et al.
Plos One, 2018
A combined approach of multiscale texture analysis and interest point/corner detectors for microcalcifications diagnosis
Liliana Losurdo, Annarita Fanizzi, Teresa M. A. Basile, Roberto Bellotti, Ubaldo Bottigli, et al.
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
A Gradient-Based Approach for Breast DCE-MRI Analysis
L. Losurdo, T. M. A. Basile, A. Fanizzi, R. Bellotti, U. Bottigli, et al.
Biomed Research International, 2018
Multivariate regression analysis of structural MRI connectivity matrices in Alzheimer’s disease
Javier Rasero, Nicola Amoroso, Marianna La Rocca, Sabina Tangaro, Roberto Bellotti, et al.
Plos One, 2017
A fuzzy-based system reveals Alzheimer's Disease onset in subjects with Mild Cognitive Impairment
Sabina Tangaro, Annarita Fanizzi, Nicola Amoroso, Roberto Bellotti
Physica Medica, 2017
DTI measurements for Alzheimer's classification
Tommaso Maggipinto, Roberto Bellotti, Nicola Amoroso, Domenico Diacono, Giacinto Donvito, et al.
Physics in Medicine and Biology, 2017
Topological Measurements of DWI Tractography for Alzheimer's Disease Detection
Nicola Amoroso, Alfonso Monaco, Sabina Tangaro, Alzheimer’s Disease Neuroimaging Initiative
Computational and Mathematical Methods in Medicine, 2017
A multi-layer MRI description of Parkinson's diseas
Nicola Amoroso, Marianna La Rocca, Roberto Bellotti, Sabina Tangaro, Eufemia Lella
Proceedings of SPIE the International Society for Optical Engineering, 2017
Salient networks: A novel application to study brain connectivity
Nicola Amoroso, Roberto Bellotti, Domenico Diacono, Marianna La Rocca, Sabina Tangaro
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2017
A multiplex network model to characterize brain atrophy in structural MRI
Marianna La Rocca, Nicola Amoroso, Roberto Bellotti, Domenico Diacono, Alfonso Monaco, et al.
Springer Proceedings in Physics, 2017
A Novel Synchronization-Based Approach for Functional Connectivity Analysis
Angela Lombardi, Sabina Tangaro, Roberto Bellotti, Alessandro Bertolino, Giuseppe Blasi, et al.
Complexity, 2017
Machine learning for the assessment of Alzheimer's disease through DTI
Nicola Amoroso, Sabina Tangaro, Eufemia Lella, Roberto Bellotti, Domenico Diacono, et al.
Proceedings of SPIE the International Society for Optical Engineering, 2017
Association between MRI structural features and cognitive measures in pediatric multiple sclerosis
Sabina Tangaro, Nicola Amoroso, Roberto Bellotti, Maria Liguori, L. Margari, et al.
Proceedings of SPIE the International Society for Optical Engineering, 2017
Hough Transform for Clustered Microcalcifications Detection in Full-Field Digital Mammograms
Teresa M. A. Basile, Annarita Fanizzi, Liliana Losurdo, Roberto Bellotti, Sonia Tangaro, et al.
Proceedings of SPIE the International Society for Optical Engineering, 2017
Topological complex networks properties for gene community detection strategy: DRD2 case study
Anna Monda, Nicola Amoroso, Teresa Maria Altomare Basile, Roberto Bellotti, Alessandro Bertolino, et al.
Springer Proceedings in Physics, 2017
MRI analysis for hippocampus segmentation on a distributed infrastructure
S. Tangaro, N. Amoroso, M. Antonacci, M. Boccardi, M. Bocchetta, et al.
2016 IEEE International Symposium on Medical Measurements and Applications Memea 2016 Proceedings, 2016
Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease
Genevera I. Allen, Nicola Amoroso, Catalina Anghel, Venkat Balagurusamy, Christopher J. Bare, et al.
Alzheimer S and Dementia, 2016
Hybrid x-space: A new approach for MPI reconstruction
A Tateo, A Iurino, G Settanni, A Andrisani, P F Stifanelli, et al.
Physics in Medicine and Biology, 2016
Automated hippocampal segmentation in 3D MRI using random undersampling with boosting algorithm
The Alzheimers Disease Neuroimaging Initiative, Rosalia Maglietta, Nicola Amoroso, Marina Boccardi, Stefania Bruno, et al.
Pattern Analysis and Applications, 2016
Integrating longitudinal information in hippocampal volume measurements for the early detection of Alzheimer's disease
Andrea Chincarini, Francesco Sensi, Luca Rei, Gianluca Gemme, Sandro Squarcia, et al.
Neuroimage, 2016
Mild traumatic brain injury outcome prediction based on both graph and K-nn methods
R. Bellotti, A. Lombardi, C. Guaragnella, N. Amoroso, A. Tateo, et al.
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2016
Medical Physics Applications in Bari ReCaS Farm
N. Amoroso, M. Antonacci, R. Bellotti, G. Donvito, R. Errico, et al.
High Performance Scientific Computing Using Distributed Infrastructures Results and Scientific Applications Derived from the Italian Pon Recas Project, 2016
Computer aided detection system for prediction of the malaise during hemodialysis
Sabina Tangaro, Annarita Fanizzi, Nicola Amoroso, Roberto Corciulo, Elena Garuccio, et al.
Computational and Mathematical Methods in Medicine, 2016
The ReCaS Project: The Bari Infrastructure
M. Antonacci, R. Bellotti, F. Cafagna, M. de Palma, D. Diacono, et al.
High Performance Scientific Computing Using Distributed Infrastructures Results and Scientific Applications Derived from the Italian Pon Recas Project, 2016
Multiple RF classifier for the hippocampus segmentation: Method and validation on EADC-ADNI Harmonized Hippocampal Protocol
P. Inglese, N. Amoroso, M. Boccardi, M. Bocchetta, S. Bruno, et al.
Physica Medica, 2015
Hippocampal unified multi-atlas network (HUMAN): Protocol and scale validation of a novel segmentation tool
N Amoroso, R Errico, S Bruno, A Chincarini, E Garuccio, et al.
Physics in Medicine and Biology, 2015
Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge
Esther E. Bron, Marion Smits, Wiesje M. van der Flier, Hugo Vrenken, Frederik Barkhof, et al.
Neuroimage, 2015
An hippocampal segmentation tool within an open cloud infrastructure
Nicola Amoroso, Sabina Tangaro, Rosangela Errico, Elena Garuccio, Anna Monda, et al.
Lecture Notes in Computer Science, 2015
Feature selection based on machine learning in MRIs for hippocampal segmentation
Sabina Tangaro, Nicola Amoroso, Massimo Brescia, Stefano Cavuoti, Andrea Chincarini, et al.
Computational and Mathematical Methods in Medicine, 2015
Automated voxel-by-voxel tissue classification for hippocampal segmentation: Methods and validation
S. Tangaro, N. Amoroso, M. Boccardi, S. Bruno, A. Chincarini, et al.
Physica Medica, 2014
Post-detection analysis for grating-based ultra-small angle X-ray scattering
F. Scattarella, S. Tangaro, P. Modregger, M. Stampanoni, L. De Caro, et al.
Physica Medica, 2013
Random forest classification for hippocampal segmentation in 3D MR images
Rosalia Maglietta, Nicola Amoroso, Stefania Bruno, Andrea Chincarini, Giovanni Frisoni, et al.
Proceedings 2013 12th International Conference on Machine Learning and Applications Icmla 2013, 2013
Alzheimer’s disease markers from structural MRI and FDG-PET brain images
Andrea Chincarini, Paolo Bosco, Gianluca Gemme, Silvia Morbelli, Dario Arnaldi, et al.
European Physical Journal Plus, 2012
Automated Shape Analysis landmarks detection for medical image processing
Computational Modelling of Objects Represented in Images Fundamentals Methods and Applications III Proceedings of the International Symposium Compimage 2012, 2012
Automatic lung segmentation in CT images with accurate handling of the hilar region
Giorgio De Nunzio, Eleonora Tommasi, Antonella Agrusti, Rosella Cataldo, Ivan De Mitri, et al.
Journal of Digital Imaging, 2011
Phase retrieval for X-ray in-line phase contrast imaging
Nuovo Cimento Della Societa Italiana Di Fisica C, 2011
Deconvolution by finite-size-source effects of x-ray phase-contrast images
Liberato De Caro, Francesco Scattarella, Sabina Tangaro, Daniele Pelliccia, Cinzia Giannini, et al.
Medical Physics, 2011
Digital image processing in medical applications, April 22, 2008
Sabina Tangaro, Roberto Bellotti, Francesco De Carlo, Gianfranco Gargano
Applications of Mathematics in Models Artificial Neural Networks and Arts Mathematics and Society, 2010
Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: The ANODE09 study
Bram van Ginneken, Samuel G. Armato, Bartjan de Hoop, Saskia van Amelsvoort-van de Vorst, Thomas Duindam, et al.
Medical Image Analysis, 2010
Combined mixed approach algorithm for in-line phase-contrast x-ray imaging
Liberato De Caro, Francesco Scattarella, Cinzia Giannini, Sabina Tangaro, Luigi Rigon, et al.
Medical Physics, 2010
Pleural nodule identification in low-dose and thin-slice lung computed tomography
A. Retico, M.E. Fantacci, I. Gori, P. Kasae, B. Golosio, et al.
Computers in Biology and Medicine, 2009
Summary of section "new accelerators, detectors, calculus and new technologies"
21st Conference on High Energy Physics Ifae 2009, 2009
Summary of section "new accelerators, detectors, calculus and new technologies"
Nuovo Cimento Della Societa Italiana Di Fisica C, 2009
A theoretical study on phase-contrast mammography with Thomson-scattering x-ray sources
Liberato De Caro, Cinzia Giannini, Roberto Bellotti, Sabina Tangaro
Medical Physics, 2009
An innovative lung segmentation algorithm in CT images with accurate delimitation of the hilus pulmonis
Giorgio De Nunzio, Eleonora Tommasi, Antonella Agrusti, Rosella Cataldo, Ivan De Mitri, et al.
IEEE Nuclear Science Symposium Conference Record, 2008
MAGIC-5: An Italian mammographic database of digitised images for research
S. Tangaro, R. Bellotti, F. De Carlo, G. Gargano, E. Lattanzio, et al.
Radiologia Medica, 2008
A novel Active Contour Model algorithm for contour detection in complex objects
G. Gargano, R. Bellotti, F. de Carlo, S. Tangaro, E. Tommasi, et al.
Proceedings of the 2007 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Cimsa, 2007
Ant Colonies for the reconstruction of artificial 3D Objects
P. Cerello, S.C. Cheran, G. Gargano, R. Bellotti, F. de Carlo, et al.
Proceedings of the 2007 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Cimsa, 2007
An SVM based approach for the analysis of mammography images
X. Gan, L. Kapsokalivas, A. Skaliotis, K. Steinhöfel, S. Tangaro, et al.
Aip Conference Proceedings, 2007
Distributed medical images analysis on a Grid infrastructure
R. Bellotti, P. Cerello, S. Tangaro, V. Bevilacqua, M. Castellano, et al.
Future Generation Computer Systems, 2007
Mass lesion detection in mammographic images using Haralik textural features
Proceedings of the International Symposium Compimage 2006 Computational Modelling of Objects Represented in Images Fundamentals Methods and Applications, 2007
A CAD system for nodule detection in low-dose lung CTs based on region growing and a new active contour model
R. Bellotti, F. De Carlo, G. Gargano, S. Tangaro, D. Cascio, et al.
Medical Physics, 2007
Comparative study of feature classification methods for mass lesion recognition in digitized mammograms
Nuovo Cimento Della Societa Italiana Di Fisica C, 2007
Mammogram segmentation by contour searching and mass lesions classification with neural network
D. Cascio, F. Fauci, R. Magro, G. Raso, R. Bellotti, et al.
IEEE Transactions on Nuclear Science, 2006
GPCALMA: An Italian mammographic database of digitized images for research
Adele Lauria, Raffaella Massafra, Sabina Sonia Tangaro, Roberto Bellotti, MariaEvelina Fantacci, et al.
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2006
A completely automated CAD system for mass detection in a large mammographic database
R. Bellotti, F. De Carlo, S. Tangaro, G. Gargano, G. Maggipinto, et al.
Medical Physics, 2006
Dissimilarity application for medical imaging classification
Wmsci 2005 the 9th World Multi Conference on Systemics Cybernetics and Informatics Proceedings, 2005
Classifiers trained on dissimilarity representation of medical pattern: A comparative study
Nuovo Cimento Della Societa Italiana Di Fisica C, 2005
A massive lesion detection algorithm in mammography
Francesco Fauci, Giuseppe Raso, Rosario Magro, Giustina Forni, Adele Lauria, et al.
Physica Medica, 2005
GPCALMA: A Grid-based tool for mammographic screening
S. Bagnasco, U. Bottigli, S. C. Cheran, P. Delogu, M. E. Fantacci, et al.
Methods of Information in Medicine, 2005
Mammogram segmentation by contour searching and massive lesion classification with neural network
IEEE Nuclear Science Symposium Conference Record, 2004
The MAGIC-5 project: Medical applications on a grid infrastructure connection
IEEE Nuclear Science Symposium Conference Record, 2004
Measurements of spectral and position resolution on a 16×16 pixel CZT imaging hard X-ray detector
Stefano Del Sordo, Gaetano Agnetta, B. Biondo, Ezio Caroli, Filippo Celi, et al.
Proceedings of SPIE the International Society for Optical Engineering, 2004
The CALMA system: An artificial neural network method for detecting masses and microcalcifications in digitized mammograms
A. Lauria, R. Palmiero, G. Forni, P. Cerello, B. Golosio, et al.
Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, 2004
FLUXEN portable equipment for direct X-ray spectra measurements
S. Aiello, U. Bottigli, F. Fauci, B. Golosio, D. Lo Presti, et al.
Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, 2004
Direct analysis of molybdenum target generated x-ray spectra with a portable device
S. Stumbo, U. Bottigli, B. Golosio, P. Oliva, S. Tangaro
Medical Physics, 2004
Diagnostic performance of radiologists with and without different CAD systems for mammography
Adele Lauria, Maria E. Fantacci, Ubaldo Bottigli, Pasquale Delogu, Francesco Fauci, et al.
Proceedings of SPIE the International Society for Optical Engineering, 2003
GPCALMA, a mammographic CAD in a GRID connection
U Bottigli, P Cerello, P Delogu, M.E Fantacci, F Fauci, et al.
International Congress Series, 2003
Search of microcalcification clusters with the CALMA CAD station
Maria E. Fantacci, Ubaldo Bottigli, Pasquale Delogu, Francesco Fauci, Bruno Golosio, et al.
Proceedings of SPIE the International Society for Optical Engineering, 2002
The CALMA project
S.R. Amendolia, M.G. Bisogni, U. Bottigli, A. Ceccopieri, P. Delogu, et al.
Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, 2001

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