Filipe Andrade Bernardi

@alumni.usp.br

University of São Paulo

Filipe Andrade Bernardi


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https://researchid.co/filipe.bernardi
He holds a degree in Biomedical Informatics from the University of São Paulo (2016), a master's degree in Bioengineering from the University of São Paulo (2019) and a PhD in Bioengineering from the University of São Paulo (2024). He is a researcher affiliated with the Health Intelligence Laboratory, registered and certified in the CNPq group directory (. He has experience and interest in the areas of digital health, data governance and quality, development and validation of computational models and artificial intelligence. His research work includes experience in the areas of Tuberculosis, with participation in several projects linked to the Brazilian Tuberculosis Research Network (REDE-TB). Since 2020, he has also worked in the area of ​​rare diseases, with emphasis on his work at the National Network of Rare Diseases (RARAS), where he is currently the manager of the IT team and a member of the steering committee at the National Institute of

RESEARCH, TEACHING, or OTHER INTERESTS

Health Informatics, Management of Technology and Innovation, Public Health, Environmental and Occupational Health, Reviews and References (medical)
57

Scopus Publications

Scopus Publications

  • From Spreadsheets to FHIR and Research Databases: Digitizing Medication Data in Elderly Care Within the RM4Health Project
    Vinícius Lima, Rute Almeida, Izabela Calvi, Daniela Domingues, Rafael Martins, Filipe Bernardi, Luís Conceição, Alberto Freitas
    Studies in Health Technology and Informatics, 2026
    Medication management in long-term care remains largely paper-based, resulting in fragmented records, transcription errors, and limited reuse opportunities. In the Portuguese use case of the RM4Health project, the Santa Casa da Misericórdia de Vagos adopted a structured datasheet template with embedded validations as the single point of entry for medication data. Two services were developed to convert XLS-based medication data into HL7 FHIR MedicationStatement resources and produce CSV files for semi-automated import into a REDCap database. The work also demonstrated the feasibility of converting semantically annotated REDCap exports back into FHIR resources, enabling bidirectional flows. Initial use indicates that the template is easy to adopt, while downstream partners may benefit from automated integration into clinical and research systems. This experience demonstrates how low-friction changes at the entry point, combined with open standards, can support data flows in long-term care settings.
  • Standardizing rare disease data in Brazil: a Delphi-based approach for the First National Registry
    Filipe Andrade Bernardi, Tatiana Takahasi Komoto, André Luiz Teixeira Vinci, Michele de Souza Seixas, Claudia Fernandes Lorea, Bibiana Mello de Oliveira, Diego Bettiol Yamada, Têmis Maria Felix, Domingos Alves, and
    Journal of Rare Diseases Germany, 2025
    Introduction Rare diseases (RD) are characterized by low prevalence, affecting fewer than 1 in 2,000 individuals, yet impacting millions globally. In Brazil, RD management is challenged by geographic disparities and unequal access to care. To address these gaps, the Brazilian Rare Diseases Network (RARAS) developed a Minimum Data Set (MDS) to standardize RD documentation. Objective To validate the proposed MDS through a Delphi consensus process with clinical experts. Methods This study used the Delphi method to validate the MDS, involving clinical experts. A structured questionnaire with 55 items across nine data categories was distributed via REDCap. Experts evaluated the relevance of each variable and reached a consensus, which was defined as ≥ 80% agreement. Results Fifty-two professionals were invited; 16 responded in round one, and 11 in round two. Suggestions for additions and removals were reviewed after each round. Seven data categories achieved over 81.8% agreement, reaching consensus levels between 90.9% and 100%. The final MDS includes care indicators and facilitates consistent documentation and care coordination. Conclusions This study demonstrates the value of standardized data collection in strengthening RD surveillance, clinical workflows, and research.
  • Integrating Large Language Models into Obstetric EHRs: The MedGPT Use Case in Portugal
    Vinícius Lima, Rute Almeida, Filipe Bernardi, Francisco Bischoff, Luís Conceição, Daniel Rodrigues, Ricardo Correia, Goreti Marreiros, Alberto Freitas
    Studies in Health Technology and Informatics, 2025
    ObsCare, an obstetric electronic health record system used in 20 Portuguese hospitals, has enabled the collection of longitudinal maternal health data. Within the MedGPT project, we aim to integrate fine-tuned large language models into ObsCare to summarize a pregnant patient’s health journey, provide culturally sensitive decision support, and generate personalized educational content. The project addresses critical gaps in obstetric care caused by workforce shortages, increasing C-section rates, and rising maternal age in Portugal. We describe the planned architecture, data sources, and early implementation strategies, highlighting how MedGPT will reduce clinicians’ documentation burden and enhance patient engagement. This work-in-progress reflects the preliminary results of a European collaboration to develop ethically aligned Generative AI solutions in healthcare.
  • Development of an Infrastructure and Computational Pipeline for Analyzing Rare Disease Research Data: A Case Study in the State of São Paulo, Brazil
    João Baiochi, Filipe Bernardi, Diego Yamada, Têmis Felix, Victor Ferraz, Vinícius Lima, Domingos Alves
    Procedia Computer Science, 2025
    Data reliability is crucial for enhancing healthcare and forming effective public policies, particularly in rare diseases research, where data complexity and heterogeneity pose significant challenges. In São Paulo, Brazil, the "Promotion and Strengthening of Comprehensive Care for Rare Diseases at Hospital das Clínicas de Ribeirão Preto" project developed an infrastructure and computational pipeline to address these issues. Utilizing the Research Electronic Data Capture platform and adhering to FAIR principles, the study aims to improve data integration, accessibility, and standardization for rare diseases research across Brazil. The pipeline employs a distributed analytics paradigm inspired by the "Personal Health Train" concept, ensuring data privacy by processing data at its source. It integrates Atomicity, Consistency, Isolation, and Durability properties and uses microservices-oriented architecture for data integrity. Federated learning enables complex analyses without moving sensitive data, enhancing privacy and reducing data leakage risks. Key tools include Python, Pandas, Matplotlib, Plotly, and Streamlit, with Prefect orchestrating data workflows and managing Extract, Transform, Load processes. Preliminary results show significant improvements in data quality and integration, allowing real-time data sharing and supporting evidence-based decision-making. The system effectively detects outliers, validates data fields, and maintains data privacy. This innovative approach provides comprehensive datasets for accurate analyses, informs healthcare policies, and improves patient outcomes. By aligning with international data standards and ethical guidelines, Brazil can advance rare diseases research and contribute to global efforts in understanding and treating these conditions.
  • Rare Disease Monitoring Portal in Brazil: An Integrated Approach to Geographic and Clinical Data
    Victor Cassão, Filipe Andrade Bernardi, Wendyson Duarte de Oliveira, Diego Bettiol Yamada, Vinícius Costa Lima, João Baiochi, Domingos Alves
    Procedia Computer Science, 2025
    This study presents a web portal application development to improve the management of rare diseases (RD) in Brazil by integrating clinical and geographic data. The Brazilian National Network of Rare Diseases (RARAS) coordinates care but struggles with underfunding and regulatory issues. This portal, focusing on the Clinical Hospital of Ribeirão Preto, aims to optimize resource allocation and patient management by providing real-time data visualization and spatial analysis. Using Python, Streamlit, and other geoprocessing libraries, the portal allows for detailed analysis of patient flows between their cities of residence and healthcare centers, highlighting travel distances and characteristic distribution patterns of different RD groups. The results indicate a significant improvement in monitoring, planning, and formulating more effective public policies for RD patients. The analysis revealed that patients, on average, travel 76.01 km to receive care, with distances ranging from 0.004 km to 1,897.09 km. The tool facilitates the identification of bottlenecks in the healthcare system, promoting informed decision-making by health managers.
  • Data Quality in Laboratory Indicators and Tuberculosis Control: A Case Study from the State of Sao Paulo
    Guilherme Lourenço Annelli, Filipe Bernardi, João Francisco Baiochi, Vinícius Lima, Nicolas Scarpa, Érica Chimara Silva, Domingos Alves
    Procedia Computer Science, 2025
    Tuberculosis remains the leading cause of death from infectious bacterial diseases globally, as recognized by the World Health Organization. This study explores the implementation of digital health strategies aimed at improving data quality in laboratory indicators and TB control within São Paulo, Brazil. It identifies opportunities for enhancing laboratory processes, data integrity, and disease management. A socio-technical approach was employed, fostering collaboration between system users and technical developers. Data were collected via the REDCap platform and evaluated on dimensions of accuracy, completeness, consistency, and timeliness. Analytical tools included Python libraries, the REDbox framework, and Apache Superset for data analysis, verification, validation, and visualization. The study involved 167 local laboratories from 13 Regional Laboratory Centers in São Paulo State. This research underscores the critical role of data quality in health surveillance and effective TB control. Future efforts should focus on enhancing training programs, improving system usability, and leveraging advanced data analytics tools to support ongoing improvements in TB control.
  • The Brazilian Knowledge Management Model: A Proposal to Support Rare Diseases Education and Awareness Processes
    Diego Bettiol Yamada, Filipe Andrade Bernardi, Vinícius Costa Lima, Julio Souza, João Francisco Baiochi, Victor Cassão, Victor Evangelista de Faria Ferraz, Domingos Alves
    Procedia Computer Science, 2025
    According to the World Health Organization and the Brazilian Ministry of Health recommendations, health education and awareness fundamentally determine the success of public health promotion strategies. Especially about rare diseases, these actions are necessary and relevant, given the existence of stigmas and discrimination in this area. International initiatives are taking action to address these obstacles. In Brazil, despite the institutionalization of the National Policy for Comprehensive Care for People with Rare Diseases in 2014, actions regarding health education and awareness are not always transparent and efficient in practice, making it challenging to fulfill the rights established by the constitution. Furthermore, there is a lack of information and validated knowledge about the diagnosis and treatment in some cases. Although health curricula are overloaded, it is necessary to complement teaching by proposing educational strategies and objectives about rare diseases attractively and innovatively. In this scenario, Knowledge Management plays a fundamental role as a set of technologies, methods, and procedures to improve the structuration, dissemination, use, and generation of knowledge. A Knowledge Management Plan suited to the organization’s needs allows for efficient resource allocation, better service excellence rates, and patient satisfaction. Therefore, this article aims to apply a Knowledge Management model within the Academic Complex of Health at the Ribeirão Preto Medical School Clinics Hospital - University of São Paulo. These processes will be carried out through robust scientific methods, consistent data, information and communication technologies, and internationally validated health guidelines aligned with the National Policy for Comprehensive Care for People with Rare Diseases.
  • Developing a Genomic Minimum Data Set for Rare Diseases in Brazil: A Delphi Protocol Approach
    Filipe Bernardi, Bibiana de Oliveira, José Carlos de Moraes, João Baiochi, Vinicius Lima, Victor Ferraz, Domingos Alves, Têmis Félix, Ida Schwartz
    Procedia Computer Science, 2025
    This study develops a Delphi protocol for a genomic Minimum Data Set (MDS) for rare diseases (RD) in Brazil. The goal is to standardize and enhance the diagnosis and treatment of RD by achieving expert consensus on essential genomic data. The Delphi method will involve multiple questionnaire rounds, engaging experts from the National Institute for Rare Diseases (INRaras). This approach addresses challenges like fragmented information and lack of data standardization, aiming for ethical, efficient, and standardized data collection. The methodology includes literature reviews, developing Delphi study questions, and utilizing the REDCap platform for secure data collection. Expected outcomes include practical guidelines for genomic data management, identifying research gaps, and influencing health policies. The initiative aims to improve diagnostic accuracy, personalize treatment approaches, foster inter-institutional collaboration, and ultimately advance genomic research and public health in Brazil, benefiting RD patients through better data integration and equitable access to diagnosis and treatment.
  • Enhancing Rare Disease Management and Care: Proposal of an Evidence-Based Digital Platform for Second Opinions
    Vinícius Lima, Filipe Bernardi, Diego Yamada, Victor Cassão, Francisco Barbosa-Junior, Têmis Félix, Victor Ferraz, Amaury Dal Fabbro, Domingos Alves
    Procedia Computer Science, 2025
    The management and care of rare diseases pose significant challenges due to limited evidence, scarce specialized resources, and pronounced healthcare disparities, particularly in Brazil. To address these issues, the development of the Rare Disease Second Opinion Platform is presented, an evidence-based digital solution designed to provide comprehensive second opinions for rare disease cases. The primary objectives are to streamline the process of obtaining clinical and non-clinical second opinions, enhance the educational knowledge base for healthcare professionals, and improve patient outcomes. The platform is developed using action research and a sociotechnical approach, ensuring it is user-centric and effective. Business process modeling and platform design will ensure a structured and user-friendly development. Preliminary results highlight the platform’s potential to connect patients, healthcare facilities, and specialists through a centralized web portal. The use of Generative Artificial Intelligence models will accelerate content production and query responses. The platform aims to significantly improve healthcare outcomes for rare disease patients in Brazil by providing timely access to specialist opinions and creating a comprehensive educational database.
  • Rare Diseases in the Community of Portuguese-Speaking Countries: Mapping, Advances in Digital Health, and International Cooperation
    Vinícius Lima, Filipe Bernardi, Rui Rijo, Alberto Freitas, Têmis Félix, Ida Schwartz, Adulai Rodrigues, Tomas Sanjuluca, Olímpio Zavale, Luis Madeira, Julio Souza, Domingos Alves
    Proceedings IEEE Symposium on Computer Based Medical Systems, 2025
    This work addresses the gaps in research and management of rare diseases in the Community of Portuguese-Speaking Countries. There is a lack of studies assessing rare disease-related digital and informational readiness, especially in African countries. International cooperation can lead to significant technological advances by measuring community members' digital maturity in managing health data, information systems, and medical technology. The main objectives include creating a collaborative network for rare diseases in the community, improving the registration and monitoring of patients, and promoting continuing education actions. From a scientific, technological, and innovation point of view, the project seeks to map the scenario using digital health tools, create strategies to establish and strengthen cooperation networks, define formative second opinion processes, and promote equitable access to digital health technologies to support decision-making. These actions will help to identify and fill gaps in governance processes, documentation, and practices, leading to realistic and equitable recommendations for better disease management in challenging contexts. Therefore, the cross-border collaboration is expected to promote a unified approach through the transnational sharing of scientific and clinical evidence, expanding the cooperation between team members and partner institutions.
  • Epidemiological characterization of rare diseases in Brazil: A retrospective study of the Brazilian Rare Diseases Network
    Bibiana Mello de Oliveira, Filipe Andrade Bernardi, João Francisco Baiochi, Mariane Barros Neiva, Milena Artifon, Alberto Andrade Vergara, Ana Maria Martins, Anete Sevciovic Grumach, Angelina Xavier Acosta, Antonette Souto El Husny, Bethania de Freitas Rodrigues Ribeiro, Camila Ferreira Ramos, Carlos Eduardo Steiner, Chong Ae Kim, Denise Maria Christofolini, Diego Bettiol Yamada, Ellaine Doris Fernandes Carvalho, Erlane Marques Ribeiro, Fabíola de Arruda Bastos, Faradiba Sarquis Serpa, Flávia Reseda Brandão, Giselle Maria Araujo Felix Adjuto, Isabelle Carvalho, Jonas Alex Morales Saute, Juan Clinton Llerena Junior, Larissa Souza Mario Bueno, Luiz Carlos Santana da Silva, Mara Lucia Schmitz Ferreira Santos, Marcela Câmara Machado Costa, Marcia Maria Costa Giacon Giusti, Marcial Francis Galera, Márcio Eloi Colombo Filho, Maria Denise Fernandes Carvalho de Andrade, Maria Teresinha De Oliveira Cardoso, Marilaine Matos de Menezes Ferreira, Michelle Zeny, Milena Coelho Fernandes Caldato, Ney Boa Sorte, Nina Rosa de Castro Musolino, Paula Frassinetti Vasconcelos de Medeiros, Paulo Ricardo Gazzola Zen, Raquel Tavares Boy Da Silva, Rayana Elias Maia, Rodrigo Fock, Rosemarie Elizabeth Schimidt Almeida, Solange Oliveira Rodrigues Valle, Tatiana Amorim, Thaís Bomfim Teixeira, Vania Mesquita Gadelha Prazeres, Victor Evangelista de Faria Ferraz, Vinicius Costa Lima, Wagner José Martins Paiva, Ida Vanessa Doederlein Schwartz, Domingos Alves, Têmis Maria Félix, Raras Network Group, Adlya de Sousa Melo, Adrya Rafaela da Silva Rocha, Amanda Aragão, Amanda Delfino Braccini, Amanda Maria Schmidt, Ana Mondadori dos Santos, Ana Carolina de Souza e Silva, Ana Catarina Góes Leite Lima, Anna Luiza Scasso, Anne Caroline Magalhães Oliveira, Arthur Perico, Bárbara da Silva Aniceto, Barbara Pinheiro, Beatriz Ono Badaró, Beatriz Brasil Braga, Beatriz de Oliveira Chapiesk, Beatriz Felix Pinheiro, Beatriz Pereira, Betânia de Souza Ponce, Bianca Martins, Blenda Antunes Cacique Curçino de Eça, Bruna de Souza, Brunno Busnardo Paschoalino, Bruno Valadares, Caio Lôbo de Oliveira, Camila Sales, Carine Pacheco Alexandre, Carla Desengrini Girelli, Carolina Balluz, Carolina de Paiva Farias, Carolina Oliveira Vilemar, Caroline Duarte Arrigoni, Catharina de Almeida Passos, Catharine Harumi, Cleber Barbieri, Daniel Prado, Daniela Monteiro, Dhallya Andressa da Silva Cruz, Eduardo Batista, Eduardo José Pereira Naves, Elaine Samara Pinheiro Mendes da Silva, Estela Teixeira, Fabio Amaral, Fernanda Caroline Moreira, Flavia Liberato de Souza, Flavia Boggian, Francisco André Gomes Bastos Filho, Gabriel Lima Lôla, Gabriel Pereira, Gabrielle Diehl, Giovanna Pessanha Cordeiro, Giulia Duran, Gustavo Foz Fonseca, Helena Mello, Henrique Serpa, Henrique Veiga, Ingrid Gabriel, Isabella Formenti, Isabella de Brito Ramos, Isabella Ramos Paiva, Janaina Ferreira, Jannine Barboza Rangel, Jôbert Pôrto Florêncio, Josevaldo Monteiro Maia Filho, Júlia Emily Silva Dantas, Julia Cordeiro Milke, Juliana Rios, Julya Pavao, Kahue Aluaxe Angelo, Karina Montemor Klegen de Oliveira, Katheryne Barbosa de Carvalho, Kauanne Zulszeski, Leticia Raabe Mota de Lima, Livia Polisseni Cotta Nascimento, Lorena Alves dos Santos Pereira, Lorenzo Makariewicz, Luan Junio Pereira Bittencourt, Luana Medeiros, Luana Souza Vasconcelos, Lucca Nogueira Paes Jannuzzi, Luciana Costa Pinto da Silva, Luisa Aguilar, Luiza Valeria Chibicheski, Luiza de Oliveira Simões, Maria Teresa Aires Cabral Dias, Mariana Lopes dos Santos, Mariana Pacheco Oliveira Neves, Marina Teixeira Henriques, Matheus Viganô Leal, Milena Atique Tacla, Milena Soares Souza, Moises Ribeiro da Paz, Morya Silva, Natan Soares, Nicole da Silva Gilbert, Otavio Mauricio Silva, Paula Dourado Sousa, Paulo Rocha, Raissa Emanuelle Jacob, Raissa Vieira Leite da Silva, Raniery Barros Carvalho, Raphaella Nagib Carvalho Santos, Raquel Silva, Rebeca Pedrosa Holanda, Rebeca Falcão Lopes Mourão, Ricardo Cunha de Oliveira, Rodrigo Mesquita Costa Braga, Sabrina Macely, Sergio Morais, Sheila Constância Adolfo Mabote Mucumbi, Simei Nhime, Stefanny Karla Ferreira de Sousa, Tauane Franca Rego, Thayane Holanda Gurjão, Thuanne Cidreira dos Santos Gomes, Tiago Ramos Gazineu, Victória Scheibe Machado, Victória Feitosa Muniz, Victória Rocha, Vitor Leão, Wendyson Oliveira, Willian Miguel, Yasmin de Araújo Ribeiro, Yasmin Amorim dos Santos
    Orphanet Journal of Rare Diseases, 2024
  • SISTB: A Health Information System for the Management of Tuberculosis Cases
    Vinícius Costa Lima, Nathalia Yukie Crepaldi, Filipe Andrade Bernardi, Renan Barbieri Segamarchi, Domingos Alves
    Communications in Computer and Information Science, 2024
  • Quality analysis and study of tuberculosis diagnostic data
    Ana Clara de Andrade Mioto, Pedro Emilio Andrade Martins, Gabriel Modina, Domingos Alves, Vinicius Costa Lima, Mariane Neiva, Filipe Andrade Bernardi
    Procedia Computer Science, 2024
  • OUTB: Application for decision-support in the outcomes of Tuberculosis
    Mariana Mozini, Raul Rothschild, Ana Clara Mioto, Filipe Bernardi, Vinícius Lima, Giovane Soares, Renan Segamarchi, Domingos Alves
    Procedia Computer Science, 2024
  • REDbox: a comprehensive semantic framework for data collection and management in tuberculosis research
    Vinícius Costa Lima, Rui Pedro Charters Lopes Rijo, Filipe Andrade Bernardi, Márcio Eloi Colombo Filho, Francisco Barbosa-Junior, Felipe Carvalho Pellison, Rafael Mello Galliez, Afrânio Lineu Kritski, Domingos Alves
    Scientific Reports, 2023
  • Development of a Mobile Application with Health Guidelines for TB Patients Care
    Manoela Reis, Filipe Bernardi, Vinicius Lima, Domingos Alves
    Studies in Health Technology and Informatics, 2023
  • A Computational Infrastructure for Analyzing Tuberculosis Research Data in Brazil
    Mariana Mozini, Filipe Bernardi, Ana Clara Mioto, Victor Cassão, Afrânio Kritski, Domingos Alves
    Studies in Health Technology and Informatics, 2023
  • From Raw Data to FAIR Data: The FAIRification Workflow for Brazilian Tuberculosis Research
    Filipe Bernardi, Vinicius Lima, Gabriel Sartoretto, João Baiochi, Victor Cassão, Afrânio Kritski, Rui Rijo, Domingos Alves
    Studies in Health Technology and Informatics, 2023
  • Security approaches for electronic health data handling through the Semantic Web: A scoping review
    Vinícius Costa Lima, Domingos Alves, Filipe Andrade Bernardi, Rui Pedro Charters Lopes Rijo
    Semantic Web, 2023
  • An information system for monitoring tuberculosis cases: Implementation research protocol using RE-AIM for a health region in Brazil
    Nathalia Yukie Crepaldi, Vinicius Costa Lima, Filipe Andrade Bernardi, Domingos Alves
    Procedia Computer Science, 2023
  • Web version of the protocol of the orofacial myofunctional evaluation with scores: usability and learning
    Maria Carolina Gironde Ataide, Filipe Andrade Bernardi, Paulo Mazzoncini de Azevedo Marques, Cláudia Maria de Felício
    Codas, 2023
  • Data Quality in Health Research: Integrative Literature Review
    Filipe Andrade Bernardi, Domingos Alves, Nathalia Crepaldi, Diego Bettiol Yamada, Vinícius Costa Lima, Rui Rijo
    Journal of Medical Internet Research, 2023
  • Supervised Machine Learning Techniques Applied to Medical Records Toward the Diagnosis of Rare Autoimmune Diseases
    Pedro Emilio Andrade Martins, Márcio Eloi Colombo Filho, Ana Clara de Andrade Mioto, Filipe Andrade Bernardi, Vinícius Costa Lima, Têmis Maria Félix, Domingos Alves
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2023
  • Scaling laws and spatial effects of Brazilian health regions: A research protocol
    Giovane Thomazini Soares, Diego Bettiol Yamada, Filipe Andrade Bernardi, Mariane Barros Neiva, Luis Pedro Lombardi Junior, André Luiz Teixeira Vinci, Ana Clara de Andrade Mioto, Domingos Alves
    Procedia Computer Science, 2023
  • The Minimum Data Set for Rare Diseases: Systematic Review
    Filipe Andrade Bernardi, Bibiana Mello de Oliveira, Diego Bettiol Yamada, Milena Artifon, Amanda Maria Schmidt, Victória Machado Scheibe, Domingos Alves, Têmis Maria Félix
    Journal of Medical Internet Research, 2023
  • A Web Portal for Real-Time Data Quality Analysis on the Brazilian Tuberculosis Research Network: A Case Study
    Victor Cassão, Filipe Andrade Bernardi, Vinícius Costa Lima, Giovane Thomazini Soares, Newton Shydeo Brandão Miyoshi, Ana Clara de Andrade Mioto, Afrânio Kritski, Domingos Alves
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2023
  • A proposal for a set of attributes relevant for web portal data quality: The brazilian rare disease network case
    Filipe Andrade Bernardi, Domingos Alves, Mariane Barros Neiva, Diego Bettiol Yamada, Vinicius Costa Lima, André Vinci, Giovane Thomazini, Rui Rijo, Têmis Maria Felix
    Procedia Computer Science, 2023
  • Epidemiology of rare diseases in Brazil: protocol of the Brazilian Rare Diseases Network (RARAS-BRDN)
    Têmis Maria Félix, Bibiana Mello de Oliveira, Milena Artifon, Isabelle Carvalho, Filipe Andrade Bernardi, Ida V. D. Schwartz, Jonas A. Saute, Victor E. F. Ferraz, Angelina X. Acosta, Ney Boa Sorte, Domingos Alves, Tatiana Amorim, Gisele Maria Araujo Felix Adjuto, Rosemarie Elizabeth Schimidt Almeida, Flávia Resedá Brandão, Larissa Souza Mario Bueno, Maria Denise Fernandes Carvalho de Andrade, Cristina Iacovelo Cagliari, Maria Terezinha Cardoso, Ellaine Doris Fernandes Carvalho, Marcela Câmara Machado Costa, Antonette El-Husny, Lavinia Schuler Faccini, Rodrigo Ambrosio Fock, Rodrigo Neves Florêncio, Marcial Francis Galera, Roberto Giugliani, Liane de Rosso Giuliani, Anette S. Grumach, Dafne G. Horovitz, Juan Clinton Llerena-Junior, Chong A. E. Kim, Rayana Elias Maia, Ana Maria Martins, Paula Frassinetti Vasconcelos de Medeiros, Nina Rosa de Castro Musolino, Marcelo Eidi Nita, Henrique Gil da Silva Nunesmaia, Jose Carlison Santos de Oliveira, Wagner José Martins Paiva, Helena Pimentel, Louise Lapagesse de Camargo Pinto, Vânia Mesquita Gadelha Prazeres, Betânia de Freitas Rodrigues Ribeiro, Erlane Ribeiro, Márcia Maria Jardim Rodrigues, Maria José Sparça Salles, Maria Teresa Vieira Sanseverino, Eliane Pereira dos Santos, Mara Lucia Schmitz Ferreira Santos, Flávia Mori Sarti, Luiz Carlos Santana da Silva, Raquel Tavares Boy da Silva, Carlos Eduardo Steiner, Ana Beatriz Winter Tavares, Thais Bonfim Teixeira, Alberto Vergara, Paulo Ricardo Gazzola Zen, Marcos Guimarães Zuchetti, and
    Orphanet Journal of Rare Diseases, 2022
  • National Network for Rare Diseases in Brazil: The Computational Infrastructure and Preliminary Results
    Diego Bettiol Yamada, Filipe Andrade Bernardi, Márcio Eloi Colombo Filho, Mariane Barros Neiva, Vinícius Costa Lima, André Luiz Teixeira Vinci, Bibiana Mello de Oliveira, Têmis Maria Félix, Domingos Alves
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2022
  • Knowledge Discovery in Databases: Comorbidities in Tuberculosis Cases
    Isabelle Carvalho, Mariane Barros Neiva, Newton Shydeo Brandão Miyoshi, Nathalia Yukie Crepaldi, Filipe Andrade Bernardi, Vinícius Costa Lima, Ketlin Fabri dos Santos, Ana Clara de Andrade Mioto, Mariana Tavares Mozini, Rafael Mello Galliez, Mauro Niskier Sanchez, Afrânio Lineu Kritski, Domingos Alves
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2022
  • Two-dimensional shear wave elastography predicts survival in advanced chronic liver disease
    Jonel Trebicka, Wenyi Gu, Victor de Ledinghen, Christophe Aubé, Aleksander Krag, Michael Praktiknjo, Laurent Castera, Jerome Dumortier, David Josef Maria Bauer, Mireen Friedrich-Rust, Stanislas Pol, Ivica Grgurevic, Rongqin Zheng, Sven Francque, Halima Gottfriedovà, Sanda Mustapic, Ioan Sporea, Annalisa Berzigotti, Frank Erhard Uschner, Benedikt Simbrunner, Maxime Ronot, Christophe Cassinotto, Maria Kjaergaard, Filipe Andrade, Martin Schulz, Georg Semmler, Ida Tjesic Drinkovic, Johannes Chang, Maximilian Joseph Brol, Pierre Emmanuel Rautou, Thomas Vanwolleghem, Christian P Strassburg, Jerome Boursier, Philip Georg Ferstl, Ditlev Nytoft Rasmussen, Thomas Reiberger, Valerie Vilgrain, Aymeric Guibal, Olivier Guillaud, Stefan Zeuzem, Camille Vassord, Xue Lu, Luisa Vonghia, Renata Senkerikova, Alina Popescu, Cristina Margini, Wenping Wang, Maja Thiele, Chrisitan Jansen
    Gut, 2022
  • Security framework for tuberculosis health data interoperability through the semantic web
    Vinicius Costa Lima, Felipe Carvalho Pellison, Filipe Andrade Bernardi, Domingos Alves, Rui Pedro Charters Lopes Rijo
    International Journal of Web Portals, 2021
  • A Mechanism for Verifying the Integrity and Immutability of Tuberculosis Data sing IOTA Distributed Ledger Technology
    Vinícius Lima, Filipe Bernardi, Rui Rijo, Jó Ueyama, Domingos Alves
    Studies in Health Technology and Informatics, 2021
  • Proposal for a health information management model based on Lean thinking
    Jéssica Cristina Caretta Teixeira, Filipe Andrade Bernardi, Rui Pedro Charters Lopes Rijo, Domingos Alves
    Procedia Computer Science, 2021
  • More than words: An analysis of brazilian emotions during covid-19
    Risti Revista Iberica De Sistemas E Tecnologias De Informacao, 2021
  • Unsupervised analysis of COVID-19 pandemic evolution in brazilian states
    Victor Cassão, Domingos Alves, Ana Clara de Andrade Mioto, Filipe Andrade Bernardi, Newton Shydeo Brandão Miyoshi
    Procedia Computer Science, 2021
  • TBI Score - Use of a mobile score system to aid the diagnosis of tuberculosis in children in Brazil
    Filipe Andrade Bernardi, Vinicius Costa Lima, Danilo Maglio Sampaio, Marcelo Cordeiro dos Santos, Rui Pedro Charters Lopes Rijo, Domingos Alves
    Procedia Computer Science, 2021
  • Operational modeling for testing diagnostic tools impact on tuberculosis diagnostic cascade: A model design
    Luana M.A. da Costa, Filipe Andrade Bernardi, Tiago Lara Michelin Sanches, Afranio Kritski, Rafael Mello Galliez, Domingos Alves
    Procedia Computer Science, 2021
  • A computational infrastructure for semantic data integration towards a patient-centered database for Tuberculosis care
    Vinícius Costa Lima, Filipe Andrade Bernardi, Michael Domingues, Afrânio Lineu Kritski, Rui Pedro Chaters Lopes Rijo, Domingos Alves
    Procedia Computer Science, 2021
  • The minimum dataset for rare diseases in Brazil: A systematic review protocol
    Filipe Andrade Bernardi, Diego Bettiol Yamada, Bibiana Mello de Oliveira, Vinicius Costa Lima, Têmis Maria Félix, Domingos Alves
    Procedia Computer Science, 2021
  • My Latent Tuberculosis Treatment - Mobile application to assist in adherence to latent tuberculosis treatment
    Thomaz Felipe Soares Arnizant, Filipe Andrade Bernardi, Tiago Lara Michelin Sanchez, Nathalia Yukie Crepaldi, Thiago Nascimento do Prado, Marcelle Temporim Novaes, Ethel Leonor Noia Maciel, Domingos Alves
    Procedia Computer Science, 2021
  • Mapping, infrastructure, and data analysis for the Brazilian network of rare diseases: Protocol for the RARASnet observational cohort study
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