Bridging the Gap in the Adoption of Trustworthy AI in Indian Healthcare: Challenges and Opportunities Sarat Kumar Chettri, Rup Kumar Deka, Manob Jyoti Saikia AI Switzerland, 2025 The healthcare sector in India has experienced significant transformations owing to the advancement in technology and infrastructure. Despite these transformations, there are major challenges to address critical issues like insufficient healthcare infrastructure for the country’s huge population, limited accessibility, shortage of skilled professionals, and high-quality care. Artificial intelligence (AI)-driven solutions have the potential to lessen the stress on India’s healthcare system; however, integrating trustworthy AI in the sector remains challenging due to ethical and regulatory constraints. This study aims to critically review the current status of the development of AI systems in Indian healthcare and how well it satisfies the ethical and legal aspects of AI, as well as to identify the challenges and opportunities in adoption of trustworthy AI in the Indian healthcare sector. This study reviewed 15 articles selected from a total of 1136 articles gathered from two electronic databases, PubMed and Google Scholar, as well as project websites. This study makes use of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). It finds that the existing studies mostly used conventional machine learning (ML) algorithms and artificial neural networks (ANNs) for a variety of tasks, such as drug discovery, disease surveillance systems, early disease detection and diagnostic accuracy, and management of healthcare resources in India. This study identifies a gap in the adoption of trustworthy AI in Indian healthcare and various challenges associated with it. It explores opportunities for developing trustworthy AI in Indian healthcare settings, prioritizing patient safety, data privacy, and compliance with ethical and legal standards.
Smart Healthcare System in Server-Less Environment: Concepts, Architecture, Challenges, Future Directions Rup Kumar Deka, Akash Ghosh, Sandeep Nanda, Rabindra Kumar Barik, Manob Jyoti Saikia Computers, 2024 Server-less computing is a novel cloud-based paradigm that is gaining popularity today for running widely distributed applications. When it comes to server-less computing, features are available via subscription. Server-less computing is advantageous to developers since it lets them install and run programs without worrying about the underlying architecture. A common choice for code deployment these days, server-less design is preferred because of its independence, affordability, and simplicity. The healthcare industry is one excellent setting in which server-less computing can shine. In the existing literature, we can see that fewer studies have been put forward or explored in the area of server-less computing with respect to smart healthcare systems. A cloud infrastructure can help deliver services to both users and healthcare providers. The main aim of our research is to cover various topics on the implementation of server-less computing in the current healthcare sector. We have carried out our studies, which are adopted in the healthcare domain and reported on an in-depth analysis in this article. We have listed various issues and challenges, and various recommendations to adopt server-less computing in the healthcare sector.
Image Representation of Numerical Data-points for Classification Using Convolutional Neural Network Rup Kumar Deka, Kausthav Pratim Kalita, Sarat Kumar Chettri 2023 4th International Conference on Computing and Communication Systems I3cs 2023, 2023 Higher dimensional data is a problem for classification. Researchers put forward various approaches like dimension reduction, ranking features for an optimal set, different feature extraction techniques, etc. for classification. In the current context of categorization, CNN (Convolution Neural Network) is a powerful tool, which classifies the data based on images as input. In this work, we have demonstrated a method to represent individual samples in an image, irrespective of dimension, and used CNN for classification. Further, to preserve data privacy, the images are flipped randomly (horizontal and vertical flips) for classification using CNN. The outcomes of both approaches are compared with related techniques and have shown promising results.
A Blockchain-based Model for Maternal Health Information Exchange and Prediction of Health Risks using Machine Learning Kausthav Pratim Kalita, Sarat Kumar Chettri, Rup Kumar Deka Proceedings of the International Conference on Intelligent and Innovative Technologies in Computing Electrical and Electronics Iciitcee 2023, 2023 Proper antenatal and postnatal care are necessary to safeguard a woman's health as well as the health of her unborn child. The field of maternal healthcare is witnessing a dramatic shift as a result of recent advancements and new initiatives in medical technology. Still the issues of data security, reliability, transparency, informed decisions, and accountability in providing health care services to name a few. In order to address the aforementioned issues and challenges and reduce the rate of maternal mortality, adoption of medical technology will be essential. In this study, an attempt has been made to combine blockchain and predictive data analytics using an ensemble machine learning algorithm in order to collect, analyze, and store maternal health data securely and reliably and predict the risk level of pregnancy complications. The data stored on the blockchain cannot be altered; it serves as a secure setting for storing patient information as well as an authentic source for learning data. The publicly accessible dataset has been used to train and test the proposed blockchain-based pregnancy complications prediction system. The effectiveness of the proposed system has also been evaluated.
Labelling unknown class samples Rup Kumar Deka International Conference on Electrical Computer Communications and Mechatronics Engineering Iceccme 2021, 2021 In a practical world, any living being survives through life long learning process. In computation, generic machine learning models are close-set recognition oriented. To create life long machine learning model, algorithms need to deal with the open-set recognition process. In this work, we have proposed a framework to recognize unknown samples of an unknown class and label them with an appropriate class label. We design decision criteria based on the knowledge of the existing two known classes and applied them to the pool of samples containing unknown samples. Experimental results show that our approach provides similar accuracy as the normal closed-set classification process, and thus, it establishes the correctness of our approach.
DDoS Attacks: Tools, Mitigation Approaches, and Probable Impact on Private Cloud Environment R. K. Deka, D. K. Bhattacharyya, J. K. Kalita Big Data Analytics for Internet of Things, 2021 The future of the Internet is predicted to be on the cloud, resulting in more complex and more intensive computing, but possibly also a more insecure digital world. The presence of a large amount of resources organized densely is a key factor in attracting DDoS attacks. Such attacks are arguably more dangerous in private individual clouds with limited resources. This paper discusses several prominent approaches introduced to counter DDoS attacks in private clouds. We also discuss issues and challenges to mitigate DDoS attacks in private clouds.
LSTM-Based Event Detection in a Stream of Assamese Text S Kalita, SK Sarma, KA Borbora, RK Deka, S Adhyapok, U Barman Proceedings of Fifth Emerging Trends and Technologies on Intelligent Systems … , 2025 2025
Iot and computer vision in smart irrigation: A review of cost-effective solutions and future trends RK Deka, MJ Saikia Preprints , 2025 2025 Citations: 1
Bridging the Gap in the Adoption of Trustworthy AI in Indian Healthcare: Challenges and Opportunities SK Chettri, RK Deka, MJ Saikia Artificial Intelligence 6 (1), 10 , 2025 2025 Citations: 19
Smart Healthcare System in Server-Less Environment: Concepts, Architecture, Challenges, Future Directions RK Deka, A Ghosh, S Nanda, RK Barik, MJ Saikia Computers 13 (4), 105 , 2023 2023 Citations: 8
Image Representation of Numerical Data-points for Classification Using Convolutional Neural Network RK Deka, KP Kalita, SK Chettri 2023 4th International Conference on Computing and Communication Systems … , 2023 2023 Citations: 2
A blockchain-based model for maternal health information exchange and prediction of health risks using machine learning KP Kalita, SK Chettri, RK Deka 2023 International Conference on Intelligent and Innovative Technologies in … , 2023 2023 Citations: 13
Analyzing Behavior to Detect Cervical Cancer RK Deka Proceedings of International Conference on Frontiers in Computing and … , 2022 2022
Labelling Unknown Class Samples RK Deka 2021 International Conference on Electrical, Computer, Communications and … , 2021 2021
A Smart feature reduction approach to detect botnet attack in IoT RK Deka, KP Kalita, DK Bhattacharyya, D Boro Emerging Technologies for Smart Cities: Select Proceedings of EGTET 2020, 17-23 , 2021 2021 Citations: 2
Integration of IoT and blockchain technology for smart cities JC Kharbhih, KP Kalita, RK Deka Emerging Technologies for Smart Cities: Select Proceedings of EGTET 2020, 1-7 , 2021 2021 Citations: 3
DDoS Attacks: Tools, Mitigation Approaches, and Probable Impact on Private Cloud Environment RK Deka, DK Bhattacharyya, JK Kalita Big Data Analytics for Internet of Things 1 , 2021 2021 Citations: 26
Network Anomaly Detection and Prevention using Statistical and Machine Learning Approaches RK Deka Tezpur University , 2019 2019 Citations: 1
Active learning to detect DDoS attack using ranked features RK Deka, DK Bhattacharyya, JK Kalita Computer Communications 145, 203-222 , 2019 2019 Citations: 61
Granger Causality in TCP Flooding Attack RK Deka, DK Bhattacharyya, JK Kalita International Journal of Network Security 21 (1), 30-39 , 2019 2019 Citations: 11
Self‐similarity based DDoS attack detection using Hurst parameter RK Deka, DK Bhattacharyya Security and Communication networks 9 (17), 4468-4481 , 2016 2016 Citations: 68
Network defense: Approaches, methods and techniques RK Deka, KP Kalita, DK Bhattacharya, JK Kalita Journal of Network and Computer Applications 57, 71-84 , 2015 2015 Citations: 46
A Secured Template Based Face Recognition Technique M Gogoi, RK Deka, D Mazumdar, M Barman, R Das IEEE Trans. on Circuits and Systems for Video Technology, 153-166 , 2012 2012 Citations: 5
MOST CITED SCHOLAR PUBLICATIONS
Self‐similarity based DDoS attack detection using Hurst parameter RK Deka, DK Bhattacharyya Security and Communication networks 9 (17), 4468-4481 , 2016 2016 Citations: 68
Active learning to detect DDoS attack using ranked features RK Deka, DK Bhattacharyya, JK Kalita Computer Communications 145, 203-222 , 2019 2019 Citations: 61
Network defense: Approaches, methods and techniques RK Deka, KP Kalita, DK Bhattacharya, JK Kalita Journal of Network and Computer Applications 57, 71-84 , 2015 2015 Citations: 46
DDoS Attacks: Tools, Mitigation Approaches, and Probable Impact on Private Cloud Environment RK Deka, DK Bhattacharyya, JK Kalita Big Data Analytics for Internet of Things 1 , 2021 2021 Citations: 26
Bridging the Gap in the Adoption of Trustworthy AI in Indian Healthcare: Challenges and Opportunities SK Chettri, RK Deka, MJ Saikia Artificial Intelligence 6 (1), 10 , 2025 2025 Citations: 19
A blockchain-based model for maternal health information exchange and prediction of health risks using machine learning KP Kalita, SK Chettri, RK Deka 2023 International Conference on Intelligent and Innovative Technologies in … , 2023 2023 Citations: 13
Granger Causality in TCP Flooding Attack RK Deka, DK Bhattacharyya, JK Kalita International Journal of Network Security 21 (1), 30-39 , 2019 2019 Citations: 11
Smart Healthcare System in Server-Less Environment: Concepts, Architecture, Challenges, Future Directions RK Deka, A Ghosh, S Nanda, RK Barik, MJ Saikia Computers 13 (4), 105 , 2023 2023 Citations: 8
A Secured Template Based Face Recognition Technique M Gogoi, RK Deka, D Mazumdar, M Barman, R Das IEEE Trans. on Circuits and Systems for Video Technology, 153-166 , 2012 2012 Citations: 5
Integration of IoT and blockchain technology for smart cities JC Kharbhih, KP Kalita, RK Deka Emerging Technologies for Smart Cities: Select Proceedings of EGTET 2020, 1-7 , 2021 2021 Citations: 3
Image Representation of Numerical Data-points for Classification Using Convolutional Neural Network RK Deka, KP Kalita, SK Chettri 2023 4th International Conference on Computing and Communication Systems … , 2023 2023 Citations: 2
A Smart feature reduction approach to detect botnet attack in IoT RK Deka, KP Kalita, DK Bhattacharyya, D Boro Emerging Technologies for Smart Cities: Select Proceedings of EGTET 2020, 17-23 , 2021 2021 Citations: 2
Iot and computer vision in smart irrigation: A review of cost-effective solutions and future trends RK Deka, MJ Saikia Preprints , 2025 2025 Citations: 1
Network Anomaly Detection and Prevention using Statistical and Machine Learning Approaches RK Deka Tezpur University , 2019 2019 Citations: 1
LSTM-Based Event Detection in a Stream of Assamese Text S Kalita, SK Sarma, KA Borbora, RK Deka, S Adhyapok, U Barman Proceedings of Fifth Emerging Trends and Technologies on Intelligent Systems … , 2025 2025
Analyzing Behavior to Detect Cervical Cancer RK Deka Proceedings of International Conference on Frontiers in Computing and … , 2022 2022
Labelling Unknown Class Samples RK Deka 2021 International Conference on Electrical, Computer, Communications and … , 2021 2021
