Dr Pinaki Ghosh

@sageuniversity.edu.in

Professor
Sanjeev Agrawal Global Educational University, Bhopal

Dr Pinaki Ghosh


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https://researchid.co/pinakiag

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Artificial Intelligence
19

Scopus Publications

413

Scholar Citations

11

Scholar h-index

13

Scholar i10-index

Scopus Publications

  • Analysis of Liver Disease Diagnosis Using Machine Learning Techniques
    Priyanka Thakur, Pinaki Ghosh
    Lecture Notes in Networks and Systems, 2026
  • Optimized Cardiovascular Disease Prediction Using Stochastic L1 Regularization and SHAP-Based Interpretability
    Irfan Khan, Pinaki Ghosh
    2nd Asian Conference on Intelligent Technologies Acoit 2025, 2025
    Cardiovascular disease remains a leading cause of death worldwide. Thus, there is a need for predictive models with adequate accuracy for early diagnosis and intervention of the disease. Artificial neural networks have shown potential in this domain because they can handle complicated and nonlinear relationships in medical data. However, ANNs tend to overfit on high-dimensional datasets with small sample sizes, which can impact their ability to generalize. In this study, we present a novel regularization technique named Stochastic L1 regularization with layer-wise probabilities. This approach applies the L1 penalty randomly to weights, with each layer having its own probability, promoting adaptive sparsity. It enhances generalization and supports more effective feature selection. Furthermore, SHAP (SHapley Additive exPlanations) utilizes the contribution of each feature in the prediction, thereby promoting transparency and clinical use of any given model. On a common CVD dataset, the stochastic L1-regularized ANN attained an accuracy of 97%, a precision of 98%, a recall of 96%, and an F1 score of 97%.
  • Optimal Predictive Model for Cardiovascular Disease Using Deep Feed-Forward Neural Network
    Irfan Khan, Pinaki Ghosh
    Smart Innovation Systems and Technologies, 2025
  • Pneumonia Detection and Chest X-Rays: Comprehensive Analysis of Artificial Intelligence Techniques in Clinical and Radiological Insights
    Mohini Gahlot, Pinaki Ghosh
    2nd International Conference on Intelligent Cyber Physical Systems and Internet of Things Icoici 2024 Proceedings, 2024
    Pneumonia continues to pose a considerable worldwide health burden, contributing significantly to morbidity and death across all age categories. The goal of this thorough Analysis study is to provide a thorough analysis of pneumonia, including information on its Pathophysiology, diagnostics, epidemiology, and treatment techniques. We'll investigate epidemiological elements using machine learning and deep learning such as incidence, prevalence, and risk factors to learn more about the disease's using artificial intelligence regional and demographic differences. The intricate Pathophysiology of pneumonia will be covered in detail, along with how host variables, environmental factors, and microbial agents interact. The merits and limits of various diagnostic procedures, such as sophisticated imaging, laboratory techniques, and clinical evaluation, will be analyzed critically. In addition, the discussion will go over current protocols and recommendations for treating pneumonia, stressing the need of supportive care, antibiotic treatment, and preventative measures. In order to provide physicians, researchers, and policymakers a thorough grasp of this common respiratory ailment, the article will discuss recent trends, difficulties, and future prospects in pneumonia research and clinical practice in using machine learning and deep learning.
  • A Hybrid Model for Sentiment Analysis Based on Movie Review Datasets
    Kirti Jain, Pinaki Ghosh, Shital Gupta
    International Journal on Recent and Innovation Trends in Computing and Communication, 2023
    The classification of sentiments, often known as sentiment analysis, is now widely recognized as an open field of research. Over the past few years, a huge amount of study work has been carried out in these disciplines by utilizing a wide variety of research approaches. Due to the possibility that the performance of sentiment analysis may be impacted by the high-dimensional feature set, text mining demands careful consideration during in the construction and selection of features.The process of recognising and extracting subjective information from written data is referred to as sentiment analysis. Sentiment analysis enables companies to understand the social sentiment around their brand, product, or service by monitoring the conversations that take place in internet chat rooms. In order to categorise people's attitudes or sentiments, this study provides a hybrid model (Support Vector Machine, Convolutional Neural Network, and Long Short-Term Memory). The findings of using the network model to sentiment analysis on the movie review or amazon review datasets reveal that it is possible to gain a good classification impact by using the model. The preprocessing is used for text mining, the removal of punctuation, and the generation of vocabulary, also uses GLOVE for vectorization and TF-IDF algorithms for better feature extraction. The results that were proposed were compared with various base models such as KNN, and MNB, amongst others, which demonstrates that the hybrid model performs better than other models.
  • Empowering Smart Cities: A Comprehensive Edge Computing Framework for Enhanced IoT Situation Awareness
    Pooja Vishwakarma, Pinaki Ghosh
    Proceedings of the 2023 IEEE International Conference on Computer Vision and Machine Intelligence Cvmi 2023, 2023
    The Internet of Things (IoT) / Web of Things (WoT) presents numerous advantages for the development of intelligent cities. With the help of a vast array of diverse IoT devices, these cities can collect a tremendous amount of data, opening up opportunities for advanced analysis and insights. Given the diversity of information sources in smart cities, processing these data and extracting meaningful insights for decision-makers is a significant hurdle. While the conventional cloud computing paradigm offers substantial computing and storage capabilities for this purpose, it necessitates transferring all data from user endpoint edge equipment to the cloud, thereby causing considerable latency. Our study aims to mitigate the latency issue in data processing by utilizing the edge computing technique. Since a significant amount of data originates from user endpoint devices, handling the data at the edge can enhance overall performance. Our findings reveal that conducting raw IoT data processing at the edge devices yields a seamless situational awareness for smart city decision-makers while minimizing latency.
  • Artificial Intelligence Based Virtual Machine Allocation and Migration Policy using Improved MBFD
    Gurpreet Singh, Lekha Rani, Pinaki Ghosh, Subhanshu Goyal, Amit Vajpayee
    Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology Ccet 2022, 2022
    With rising demand and an increase in the number of servers in data centres, cloud computing is a new era of technology that is based on pay-per-use. As the number of servers rises, so do the virtual machines (VMs), which must be distributed among physical hosts to satisfy client demands. These VMs must be appropriately assigned; otherwise, their erroneous allocation increases energy consumption. This can be avoided by reallocating these VMs to a suitable physical host that can accommodate their needs. The mechanism for allocating and migrating virtual machines is presented in this work. With the aid of our suggested optimization technique, the uniqueness in the two primary virtualization processes- VM allocation and VM migration-was explained in this study. In terms of VM allocation and migration, the proposed study reduced energy consumption relative to earlier research. The proposed work is broken down into two main sections: 1. VM allocation using Improved MBFD. b. SVM-based allocation verification to cut down on false migrations. This article is divided into five sections: Section 1 introduces virtualization, VM allocation, and migration; A brief summary of the literature is presented in Section 2, while Section 3 provides a suggested allocation and migration policy using an improved MBFD; and Section 4 offers results and discussion, followed by a conclusion and discussion of the article's future directions.
  • Breast Cancer Detection in the IoT Cloud-based Healthcare Environment Using Fuzzy Cluster Segmentation and SVM Classifier
    Umesh Kumar Lilhore, Sarita Simaiya, Himanshu Pandey, Vinay Gautam, Atul Garg, Pinaki Ghosh
    Lecture Notes in Networks and Systems, 2022
  • Precise Forecasting of Stock Market Pricing Using Weighted Ensemble Machine Learning Method
    Umesh Kumar Lilhore, Sarita Simaiya, Advin Manhar, Shilpi Harnal, Pinaki Ghosh, Atul Garg
    Lecture Notes in Electrical Engineering, 2022
  • Role of Swarm Intelligence and Artificial Neural Network Methods in Intelligent Traffic Management
    Umesh Kumar Lilhore, Sarita Simaiya, Pinaki Ghosh, Atul Garg, Naresh Kumar Trivedi, Abhineet Anand
    Smart Innovation Systems and Technologies, 2022
  • A Machine Learning-based Automatic Model to Predicting Performance of Students
    Atul Garg, Nidhi Bansal Garg, Pinaki Ghosh, Ankit Bansal, Umesh Kumar Lilhore, Sarita Simaiya
    Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology Ccet 2022, 2022
  • Prediction of the Risk of Heart Attack Using Machine Learning Techniques
    Pinaki Ghosh, Umesh Kumar Lilhore, Sarita Simaiya, Atul Garg, Devendra Prasad, Ajay Kumar
    Lecture Notes in Electrical Engineering, 2022
  • IoT based Smart Healthcare Monitoring Systems: A Review
    Divyanshu Tiwari, Devendra Prasad, Kalpna Guleria, Pinaki Ghosh
    Proceedings of IEEE International Conference on Signal Processing Computing and Control, 2021
  • Machine Learning-based Model for Prediction of Student's Performance in Higher Education
    Atul Garg, Umesh Kumar Lilhore, Pinaki Ghosh, Devendra Prasad, Sarita Simaiya
    Proceedings of the 8th International Conference on Signal Processing and Integrated Networks Spin 2021, 2021
  • EEPSA: Energy Efficiency Priority Scheduling Algorithm for Cloud Computing
    Sarita Simaiya, Vinay Gautam, Umesh Kumar Lilhore, Atul Garg, Pinaki Ghosh, Naresh Kumar Trivedi, Abhineet Anand
    Proceedings 2nd International Conference on Smart Electronics and Communication Icosec 2021, 2021
  • FOREX trend analysis using machine learning techniques: INR vs USD currency exchange rate using ANN-GA hybrid approach
    Pradeepta Kumar Sarangi, Muskaan Chawla, Pinaki Ghosh, Sunny Singh, P.K. Singh
    Materials Today Proceedings, 2020
  • Untraceable privacy-preserving authentication protocol for RFID tag using salted hash algorithm
    Pinaki Ghosh, T.R. Mahesh
    International Journal of Advanced Intelligence Paradigms, 2019
  • A privacy preserving mutual authentication protocol for RFID based automated toll collection system
    Pinaki Ghosh, Mahesh T R
    Proceedings of 2016 International Conference on ICT in Business Industry and Government Ictbig 2016, 2017
  • Design of new security algorithm: Using hybrid Cryptography architecture
    Manali J Dubai, T R Mahesh, Pinaki A Ghosh
    Icect 2011 2011 3rd International Conference on Electronics Computer Technology, 2011

RECENT SCHOLAR PUBLICATIONS

  • Optimized Cardiovascular Disease Prediction Using Stochastic L1 Regularization and SHAP-Based Interpretability
    I Khan, P Ghosh
    2025 2nd Asian Conference on Intelligent Technologies (ACOIT), 1-6 , 2025
    2025
  • Analysis of Liver Disease Diagnosis Using Machine Learning Techniques
    P Thakur, P Ghosh
    International Conference on Innovations in Data Science, 67-75 , 2024
    2024
  • Pneumonia Detection and Chest X-Rays: Comprehensive Analysis of Artificial Intelligence Techniques in Clinical and Radiological Insights
    M Gahlot, P Ghosh
    2024 Second International Conference on Intelligent Cyber Physical Systems … , 2024
    2024
  • INVESTIGATING THE INTERPLAY OF EDGE COMPUTING AND IOT IN SMART CITIES
    P Vishwakarma, P Ghosh
    Journal of Data Acquisition and Processing 39 (1), 1566-1583 , 2024
    2024
  • A Review of Recent Studies on Prediction of Cardiovascular Disease
    I Khan, P Ghosh
    IJAETS 5 (1) , 2024
    2024
  • Analyzing the Sentiment of Social-Media for Predicting Depression using Supervised Learning and Radial Basis Function
    Y Sahu, P Ghosh
    2024
  • Smartphones Capturing Gait Biometrics-A Deep Learning Paradigm
    M Parihar, P Ghosh
    2024
  • Technological Breakthroughs Shaping Smart Energy Administration in Urban Centres
    P Vishwakarma, P Ghosh
    2024
  • A Brief Survey on Techniques for Protein Sequence Analysis
    P Pawar, P Ghosh
    2024
  • Empowering Smart Cities: A Comprehensive Edge Computing Framework for Enhanced IoT Situation Awareness
    P Vishwakarma, P Ghosh
    2023 IEEE International Conference on Computer Vision and Machine … , 2023
    2023
  • Introduction To IOT And Its Applications
    P Ghosh, K Jain, MC Kumar, MK Jha
    Academic Guru Publishing House , 2023
    2023
    Citations: 2
  • Understanding Machine Learning
    P Ghosh, S Kiran, J Mahalakshmi, SKAH Basha
    AG PUBLISHING HOUSE (AGPH Books) , 2023
    2023
    Citations: 6
  • Sentiment Analysis of Depression Prediction from Social-Media: A Comprehensive
    Y Sahu, P Ghosh, G Shrivastava, K Jain, S SSAC
    2023
  • A Hybrid Model for Sentiment Analysis Based on Movie Review Datasets
    K Jain, P Ghosh, S Gupta
    Int. J. Recent Innov. Trends Comput. Commun 11, 424-431 , 2023
    2023
    Citations: 7
  • Artificial Intelligence Based Virtual Machine Allocation and Migration Policy using Improved MBFD
    G Singh, L Rani, P Ghosh, S Goyal, A Vajpayee
    2022 IEEE International Conference on Current Development in Engineering and … , 2022
    2022
    Citations: 14
  • A Machine Learning-based Automatic Model to Predicting Performance of Students
    A Garg, NB Garg, P Ghosh, A Bansal, UK Lilhore, S Simaiya
    2022 IEEE International Conference on Current Development in Engineering and … , 2022
    2022
    Citations: 5
  • Optimal Predictive Model for Cardiovascular Disease Using Deep Feed-Forward Neural Network
    I Khan, P Ghosh
    Congress on Smart Computing Technologies, 193-204 , 2022
    2022
  • Prediction of the Risk of Heart Attack Using Machine Learning Techniques
    P Ghosh, UK Lilhore, S Simaiya, A Garg, D Prasad, A Kumar
    Data, Engineering and Applications: Select Proceedings of IDEA 2021, 613-621 , 2022
    2022
    Citations: 11
  • Precise Forecasting of Stock Market Pricing Using Weighted Ensemble Machine Learning Method
    UK Lilhore, S Simaiya, A Manhar, S Harnal, P Ghosh, A Garg
    Data, Engineering and Applications: Select Proceedings of IDEA 2021, 637-647 , 2022
    2022
    Citations: 2
  • Breast Cancer Detection in the IoT Cloud-based Healthcare Environment Using Fuzzy Cluster Segmentation and SVM Classifier
    UK Lilhore, S Simaiya, H Pandey, V Gautam, A Garg, P Ghosh
    Ambient Communications and Computer Systems: Proceedings of RACCCS 2021, 165-179 , 2022
    2022
    Citations: 53

MOST CITED SCHOLAR PUBLICATIONS

  • Breast Cancer Detection in the IoT Cloud-based Healthcare Environment Using Fuzzy Cluster Segmentation and SVM Classifier
    UK Lilhore, S Simaiya, H Pandey, V Gautam, A Garg, P Ghosh
    Ambient Communications and Computer Systems: Proceedings of RACCCS 2021, 165-179 , 2022
    2022
    Citations: 53
  • FOREX trend analysis using machine learning techniques: INR vs USD currency exchange rate using ANN-GA hybrid approach
    PK Sarangi, M Chawla, P Ghosh, S Singh, PK Singh
    Materials Today: Proceedings 49, 3170-3176 , 2022
    2022
    Citations: 47
  • IoT based Smart Healthcare Monitoring Systems: A Review
    D Tiwari, D Prasad, K Guleria, P Ghosh
    2021 6th International Conference on Signal Processing, Computing and … , 2021
    2021
    Citations: 39
  • Machine Learning-based Model for Prediction of Student’s Performance in Higher Education
    A Garg, UK Lilhore, P Ghosh, D Prasad, S Simaiya
    2021 8th International Conference on Signal Processing and Integrated … , 2021
    2021
    Citations: 35
  • Design of new security algorithm: Using hybrid Cryptography architecture
    MJ Dubai, TR Mahesh, PA Ghosh
    Electronics Computer Technology (ICECT), 2011 3rd International Conference … , 2011
    2011
    Citations: 32
  • Smart City: Concept and Challenges
    P Ghosh, TR Mahesh
    Int. J. on Advances in Engineering, Technology and Science 1 (1) , 2015
    2015
    Citations: 31
  • A privacy preserving mutual authentication protocol for RFID based automated toll collection system
    P Ghosh, TR Mahesh
    2016 International Conference on ICT in Business Industry & Government … , 2016
    2016
    Citations: 24
  • EEPSA: Energy Efficiency Priority Scheduling Algorithm for Cloud Computing
    S Simaiya, V Gautam, UK Lilhore, A Garg, P Ghosh, NK Trivedi, A Anand
    2021 2nd International Conference on Smart Electronics and Communication … , 2021
    2021
    Citations: 19
  • Design of a new security protocol using hybrid cryptography architecture
    MJ Dubal, TR Mahesh, PA Ghosh
    Proceedings of 3rd International Conference on Electronics Computer … , 2011
    2011
    Citations: 16
  • Breast cancer detection using genetic algorithm with correlation based feature selection: experiment on different datasets
    S Singla, P Ghosh, U Kumari
    International Journal of Computer Sciences and Engineering 7 (4), 406-410 , 2019
    2019
    Citations: 15
  • Artificial Intelligence Based Virtual Machine Allocation and Migration Policy using Improved MBFD
    G Singh, L Rani, P Ghosh, S Goyal, A Vajpayee
    2022 IEEE International Conference on Current Development in Engineering and … , 2022
    2022
    Citations: 14
  • Prediction of the Risk of Heart Attack Using Machine Learning Techniques
    P Ghosh, UK Lilhore, S Simaiya, A Garg, D Prasad, A Kumar
    Data, Engineering and Applications: Select Proceedings of IDEA 2021, 613-621 , 2022
    2022
    Citations: 11
  • Group caching: A novel cooperative caching scheme for mobile ad hoc networks
    SN Trambadiya, PA Ghosh, JN Rathod
    Int. J. Eng. Res. Develop. 6 (11), 23-30 , 2013
    2013
    Citations: 11
  • A Hybrid Model for Sentiment Analysis Based on Movie Review Datasets
    K Jain, P Ghosh, S Gupta
    Int. J. Recent Innov. Trends Comput. Commun 11, 424-431 , 2023
    2023
    Citations: 7
  • Evaluation of Cooperative Black Hole Attack in AODV Routing Protocol in MANET
    R Goyal, PA Ghosh
    BLB-International Journal of Science & Technology 1 (2), 161-170 , 2010
    2010
    Citations: 7
  • Understanding Machine Learning
    P Ghosh, S Kiran, J Mahalakshmi, SKAH Basha
    AG PUBLISHING HOUSE (AGPH Books) , 2023
    2023
    Citations: 6
  • Untraceable privacy-preserving authentication protocol for RFID tag using salted hash algorithm
    P Ghosh, TR Mahesh
    International Journal of Advanced Intelligence Paradigms 13 (1-2), 193-209 , 2019
    2019
    Citations: 6
  • Identification and Elimination of Selfish Nodes in Adhoc Network
    S Nagar, D Raimagia, P Ghosh
    International Journal of Engineering Research and Development 10 (4), 29-34 , 2014
    2014
    Citations: 6
  • A Machine Learning-based Automatic Model to Predicting Performance of Students
    A Garg, NB Garg, P Ghosh, A Bansal, UK Lilhore, S Simaiya
    2022 IEEE International Conference on Current Development in Engineering and … , 2022
    2022
    Citations: 5
  • Role of Swarm Intelligence and Artificial Neural Network Methods in Intelligent Traffic Management
    UK Lilhore, S Simaiya, P Ghosh, A Garg, NK Trivedi, A Anand
    Machine Learning and Autonomous Systems: Proceedings of ICMLAS 2021, 209-222 , 2022
    2022
    Citations: 4