Protecting Personal Healthcare Record Using Blockchain & Federated Learning Technologies

Advances and Open Problems in Federated Learning

Kairouz, P., & McMahan, H. B. (2021) · Foundations and Trends in Machine Learning · doi:10.1561/2200000083 · Cited by 7,772 · see citing works

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

Gulshan, V., Peng, L., Coram, M., Stumpe, M. C., Wu, D., Narayanaswamy, A., Venugopalan, S., Widner, K., Madams, T., Cuadros, J., et al. (2016) · JAMA · doi:10.1001/jama.2016.17216 · Cited by 7,697 · see citing works

Federated Machine Learning: Concept and Applications

Yang, Q., Liu, Y., Chen, T., & Tong, Y. (2019) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3298981 · Cited by 6,322 · see citing works

Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning

Kermany, D. S., Goldbaum, M., Cai, W., Valentim, C. C. S., Liang, H., Baxter, S. L., McKeown, A., Yang, G., Wu, X., Yan, F., et al. (2018) · Cell · doi:10.1016/j.cell.2018.02.010 · Cited by 4,842 · see citing works

The future of digital health with federated learning

Rieke, N., Hancox, J., Li, W., Milletarì, F., Roth, H. R., Albarqouni, S., Bakas, S., Galtier, M. N., Landman, B. A., Maier-Hein, K., et al. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-00323-1 · Cited by 3,119 · see citing works

Automated detection of COVID-19 cases using deep neural networks with X-ray images

Öztürk, T., Talo, M., Yildirim, E. A., Baloğlu, U. B., Yıldırım, Ö., & Acharya, U. R. (2020) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2020.103792 · Cited by 2,607 · see citing works

Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation

Sheller, M. J., Reina, G. A., Edwards, B., Martin, J., & Bakas, S. (2019) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-11723-8_9 · Cited by 609 · see citing works

Privacy-Preserving Federated Brain Tumour Segmentation

Li, W., Milletarì, F., Xu, D., Rieke, N., Hancox, J., Zhu, W., Baust, M., Cheng, Y., Ourselin, S., Cardoso, M. J., et al. (2019) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-32692-0_16 · Cited by 578 · see citing works

Deep learning based detection and analysis of COVID-19 on chest X-ray images

Jain, R., Gupta, M., Taneja, S., & Hemanth, D. J. (2020) · Applied Intelligence · doi:10.1007/s10489-020-01902-1 · Cited by 523 · see citing works

Blockchain in healthcare: A systematic literature review, synthesizing framework and future research agenda

Tandon, A., Dhir, A., Islam, A. K. M. N., & Mäntymäki, M. (2020) · Computers in Industry · doi:10.1016/j.compind.2020.103290 · Cited by 439 · see citing works

A framework for secure and decentralized sharing of medical imaging data via blockchain consensus

Patel, V. N. (2018) · Health Informatics Journal · doi:10.1177/1460458218769699 · Cited by 394 · see citing works

Deep Learning–based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses

Choe, J., Lee, S. M., Do, K., Lee, G., Lee, J., Lee, S. M., & Seo, J. B. (2019) · Radiology · doi:10.1148/radiol.2019181960 · Cited by 296 · see citing works

Detection of COVID-19 from Chest X-Ray Images Using Convolutional Neural Networks

Şekeroğlu, B., & Özşahin, İ. (2020) · SLAS TECHNOLOGY · doi:10.1177/2472630320958376 · Cited by 152 · see citing works

Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects

Negassi, M., Suarez-Ibarrola, R., Hein, S., Miernik, A. J., & Reiterer, A. (2020) · World Journal of Urology · doi:10.1007/s00345-019-03059-0 · Cited by 71 · see citing works

A comprehensive survey on federated learning techniques for healthcare informatics

Dasaradharami Reddy, K., & Gadekallu, T. R. (2023) · Computational Intelligence and Neuroscience · doi:10.1155/2023/8393990 · Cited by 126 · see citing works

DMFL_Net: A Federated Learning-Based Framework for the Classification of COVID-19 from Multiple Chest Diseases Using X-rays

Malik, H., Naeem, A., Naqvi, R. A., & Loh, W.-K. (2023) · Sensors · doi:10.3390/s23020743 · Cited by 97 · see citing works

Blockchain, artificial intelligence, and healthcare: the tripod of future—a narrative review

Bathula, A., Gupta, S. K., Merugu, S., Saba, L., Khanna, N. N., Laird, J. R., Sanagala, S. S., Singh, R. K., Garg, D., Fouda, M. M., et al. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10873-5 · Cited by 100 · see citing works

Enhancing trust and privacy in distributed networks: a comprehensive survey on blockchain-based federated learning

Liu, J., Chen, C., Li, Y., Sun, L., Song, Y., Zhou, J., Jing, B., & Dou, D. (2024) · Knowledge and Information Systems · doi:10.1007/s10115-024-02117-3 · Cited by 58 · see citing works

Privacy-Enhancing Technologies in Federated Learning for the Internet of Healthcare Things: A Survey

Mosaiyebzadeh, F., Pouriyeh, S., Parizi, R. M., Sheng, Q. Z., Han, M., Zhao, L., Sannino, G., Ranieri, C. M., Ueyama, J., & Batista, D. M. (2023) · Electronics · doi:10.3390/electronics12122703 · Cited by 51 · see citing works

A Survey on Secure and Private Federated Learning Using Blockchain: Theory and Application in Resource-Constrained Computing

Moore, E., Imteaj, A., Rezapour, S., & Amini, M. H. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3313055 · Cited by 52 · see citing works

Digital Anti-Aging Healthcare: An Overview of the Applications of Digital Technologies in Diet Management

Armand, T. P. T., Kim, H., & Kim, J.-I. (2024) · Journal of Personalized Medicine · doi:10.3390/jpm14030254 · Cited by 50 · see citing works

Blockchain-Based Privacy-Enhancing Federated Learning in Smart Healthcare: A Survey

Limbepe, Z. N., Gai, K., & Yu, J. (2025) · Blockchains · doi:10.3390/blockchains3010001 · Cited by 48 · see citing works

A Survey on Blockchain-Based Federated Learning

Wu, L., Ruan, W., Hu, J., & He, Y. (2023) · Future Internet · doi:10.3390/fi15120400 · Cited by 48 · see citing works

Recent Advances of Blockchain and Its Applications

Li, X., & Wu, W. (2022) · Journal of Social Computing · doi:10.23919/jsc.2022.0016 · Cited by 38 · see citing works

Applications and Challenges of Federated Learning Paradigm in the Big Data Era with Special Emphasis on COVID-19

Majeed, A., Zhang, X., & Hwang, S. O. (2022) · Big Data and Cognitive Computing · doi:10.3390/bdcc6040127 · Cited by 35 · see citing works

Leveraging Patient Information Sharing Using Blockchain-Based Distributed Networks

Barbaria, S., Mont, M. C., Ghadafi, E., Machraoui, H. M., & Rahmouni, H. B. (2022) · IEEE Access · doi:10.1109/access.2022.3206046 · Cited by 22 · see citing works

Advancing Federated Learning: A Systematic Literature Review of Methods, Challenges, and Applications

Sana, T. Z., Abdulla, S., Nag, A., Das, A., Hassan, M. M., Fiza, Z. Z., Karim, A., & Kabir, S. R. R. (2025) · IEEE Access · doi:10.1109/access.2025.3605165 · Cited by 21 · see citing works

Federated learning with deep convolutional neural networks for the detection of multiple chest diseases using chest x-rays

Malik, H., & Anees, T. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-023-18065-z · Cited by 19 · see citing works

Blockchain and machine learning in the internet of things: a review of smart healthcare

Al-Blihed, N. S., Almufadi, N., Al-Harbi, N. T., Al-Omari, I. A., & Al-Hagery, M. A. (2023) · IAES International Journal of Artificial Intelligence · doi:10.11591/ijai.v12.i3.pp995-1006 · Cited by 16 · see citing works

On the Adoption of Modern Technologies to Fight the COVID-19 Pandemic: A Technical Synthesis of Latest Developments

Majeed, A., & Zhang, X. (2023) · COVID · doi:10.3390/covid3010006 · Cited by 16 · see citing works

A systematic review of innovations for real-time image security in IoT applications using machine learning and blockchain

Rai, M., Kumar, S., & Rathore, P. S. (2024) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-024-02535-8 · Cited by 16 · see citing works

Securing Federated Learning With Blockchain in the Medical Field: Systematic Literature Review

Wang, X., Xie, Y., Chen, X., Yang, J., Li, R., Gao, W., Yan, Z., Zhou, H., & Ye, Z. (2026) · Journal of Medical Internet Research · doi:10.2196/79052 · Cited by 18 · see citing works

A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine

Shen, J. P., Ghatti, S., Levkov, N. R., Shen, H., Sen, T., Rheuban, K. S., Enfield, K., Facteau, N. R., Engel, G., & Dowdell, K. (2022) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2022.1034732 · Cited by 13 · see citing works

An analysis of decipherable red blood cell abnormality detection under federated environment leveraging XAI incorporated deep learning

Dipto, S. M., Reza, M. T., Mim, N. T., Ksibi, A., Alsenan, S. A., Uddin, J., & Samad, M. A. (2024) · Scientific Reports · doi:10.1038/s41598-024-76359-0 · Cited by 11 · see citing works

The IHI Rochester Report 2022 on Healthcare Informatics Research: Resuming After the CoViD-19

Combi, C., Facelli, J. C., Haddawy, P., Holmes, J. H., Koch, S., Liu, H., Meyer, J., Mor Peleg, B., Pozzi, G., Štiglic, G., et al. (2023) · Journal of Healthcare Informatics Research · doi:10.1007/s41666-023-00126-5 · Cited by 11 · see citing works

A Comprehensive Review of Cryptographic Techniques in Federated Learning for Secure Data Sharing and Applications

Sen, A., Heng, S., & Tan, S. C. (2025) · IEEE Access · doi:10.1109/access.2025.3593953 · Cited by 12 · see citing works

Privacy-Preserving Computing in the Healthcare Using Federated Learning

Khan, S. (2024) · Advances in marketing, customer relationship management, and e-services book series · doi:10.4018/979-8-3693-2165-2.ch015 · Cited by 10 · see citing works

Integration of Federated Learning and Blockchain in Health Care: Tutorial on Medical Data, Architectures, Privacy, Security, and Regulatory Compliance

Shahsavari, Y., Baseri, Y., Hafid, A. S., Dambri, O. A., & Makrakis, D. (2026) · Journal of Medical Internet Research · doi:10.2196/80178 · Cited by 23 · see citing works

FedMetaMed: Federated Meta-Learning for Personalized Medication in Distributed Healthcare Systems

Gao, J., & Li, Y. (2024) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm62325.2024.10821859 · Cited by 11 · see citing works

A Federated Learning Approach to Support the Decision-Making Process for ICU Patients in a European Telemedicine Network

Paragliola, G., Ribino, P., & Ullah, Z. (2023) · Journal of Sensor and Actuator Networks · doi:10.3390/jsan12060078 · Cited by 8 · see citing works

FedRx: Federated Distillation-Based Solution for Preventing Hospitals Overcrowding During Seasonal Diseases Using MEC

Sahraoui, Y., Kerrache, C. A., Calafate, C. T., & Manzoni, P. (2024) · IEEE Consumer Communications and Networking Conference · doi:10.1109/ccnc51664.2024.10454641 · Cited by 8 · see citing works

Federated learning system eliminating model drift in distributed edge computing: Theoretical analytics and application on pit engineering state monitoring

Xia, Z., Zhong, B., Zhao, T., Li, K., & Zhang, S. (2025) · Advanced Engineering Informatics · doi:10.1016/j.aei.2025.103505 · Cited by 8 · see citing works

Global data sharing of SARS-CoV-2 based on blockchain

Sajedi, H., & Mohammadipanah, F. (2023) · International Journal of Information Technology · doi:10.1007/s41870-023-01431-3 · Cited by 8 · see citing works

The Data Heterogeneity Issue Regarding COVID-19 Lung Imaging in Federated Learning: An Experimental Study

Al-Hafiz, F., & Basuhail, A. A. (2025) · Big Data and Cognitive Computing · doi:10.3390/bdcc9010011 · Cited by 7 · see citing works

A Comprehensive Distributed Framework for Cross-silo Federated Learning using Blockchain

Durgapal, P., Kataria, P., Garg, G., & Anand, A. S. (2023) · International Conference on Blockchain Computing and Applications (BCCA) · doi:10.1109/bcca58897.2023.10338869 · Cited by 7 · see citing works

Preserving Privacy and Security of Electronic Health Records using Blockchain-based Federated Learning (BFL) Framework

Gayathri Hegde, M., Shrishti Bekal, M., Shenoy, P. D., & Venugopal, K. R. (2023) · IEEE Region Humanitarian Technology Conference · doi:10.1109/r10-htc57504.2023.10461823 · Cited by 5 · see citing works

Using AI and Blockchain in Case of Algorithm Regulation

Tripathi, N., & Mishra, A. K. (2023) · International Conference for Innovation in Technology (INOCON) · doi:10.1109/inocon57975.2023.10101367 · Cited by 4 · see citing works

FedSC: A federated learning algorithm based on client-side clustering

Wang, Z., Liu, R., Xu, J., & Fu, Y. (2023) · Electronic Research Archive · doi:10.3934/era.2023266 · Cited by 4 · see citing works

Decentralized Federated Learning Loop with Constrained Trust Mechanism

Połap, D., Prokop, K., Srivastava, G., & Lin, J. C. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-42505-9_17 · Cited by 4 · see citing works

Leveraging blockchain-based healthcare services with artificial intelligence

Marković, L., Trpkov, A., Sovtić, D., Rodić, B., & Лабус, А. (2025) · International Conference on Smart and Sustainable Technologies (SpliTech) · doi:10.23919/splitech65624.2025.11091715 · Cited by 2 · see citing works

A Blockchain Patient-Centric Records Framework for Older Adult Healthcare

Osborn, S., & Choo, K. R. (2023) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-50051-0_2 · Cited by 2 · see citing works

A distributed classification and prediction model using federated learning in healthcare

Rathee, G., Singh, A., Singal, G., & Tomar, A. (2025) · Knowledge and Information Systems · doi:10.1007/s10115-025-02525-z · Cited by 1 · see citing works

Investigation on the Integrated Cloud and BlockChain (ICBC)Technologies to Secure Healthcare Data Management Systems

Badr, A. M., Fourati, L. C., & Ayed, S. (2023) · International Conference on Developments in eSystems Engineering (DeSE) · doi:10.1109/dese58274.2023.10100065 · Cited by 2 · see citing works

Digital Secure Storage for Healthcare Data Information Using Blockchain

Naveenkumar, H., & Ranjana, P. (2023) · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · doi:10.1109/icacite57410.2023.10183118

Health Prediction Web Application Using Flask Framework

(2024) · International Research Journal of Modernization in Engineering Technology and Science · doi:10.56726/irjmets50424

The Role of Machine Learning in Equipping Students with Emerging Opportunities

Sengar, A. S., Bahadure, N. B., Mishra, A. K., Chaudhari, V., Pandey, N. K., & Dumka, A. (2024) · International Conference on Smart Devices (ICSD) · doi:10.1109/icsd60021.2024.10751239

The Impact of Digital Workforce and Robotics in Ubiquitous Technology

Mishra, A. K., Bahadure, N. B., Pandey, N. K., Karnatak, V., Dumka, A., & Patni, J. C. (2024) · International Conference on Smart Devices (ICSD) · doi:10.1109/icsd60021.2024.10751642

FlexRout: Dynamic Routing in Blockchain Networks

Das, S., Tapwal, R., & Misra, S. (2024) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2024.3519802

Empowering Health Insurance with Personalization: A Comprehensive Architecture Leveraging Federated Learning and BlockChain

Jain, A., Gupta, G. V., Johari, R., & Vidyarthi, D. P. (2025) · Lecture notes in electrical engineering · doi:10.1007/978-981-97-9507-9_16

Temporal Convolution Network with Long Short-Term Memory based Predictive Diagnosis for Personalized Healthcare

Kaidhapuram, S. R., Al-Akayshee, A. S., Anu, D., Seknametla, P. R., & Dhanamalar, M. (2025) · International Conference on Intelligent Computing and Knowledge Extraction (ICICKE) · doi:10.1109/icicke65317.2025.11136460

Federated Learning for Healthcare: Analysis and Study on Heterogeneous Datasets using FedAP

Mehek, S. T., Reddy, C. K. K., Vanka, S., Alhameed, M. H., Shuaib, M., & Alam, S. (2025) · IEEE Congress on Information Science and Technology (CiSt) · doi:10.1109/cist65886.2025.11224123

A systematic survey of blockchain-enabled artificial intelligence for industrial IoT: recent advances, integration challenges, and future prospects

Rahman, A., Kundu, D., Debnath, T., Rahman, M., Islam, M. J., Farid, F. A., Karim, H. B. A., & Miah, A. S. M. (2026) · Artificial Intelligence Review · doi:10.1007/s10462-026-11612-8 · Cited by 1 · see citing works

Fog inspired IoT based smart healthcare system: recent advancements and challenges

Rai, A., & Kumar, M. (2026) · International Journal of Systems Assurance Engineering and Management · doi:10.1007/s13198-026-03405-7

Blockchain & Federated Learning Technologies for Protecting Sensitive Personal Healthcare Information

Singh, J., Ghai, K., Sharma, D., & Singla, R. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-031-78922-9_8

Multi-Continental Healthcare Modelling Using Blockchain-Enabled Federated Learning

Sun, R., Wang, Z., Zhang, H., Jiang, M., Wen, Y., Sun, J., Liu, E., & Li, K. (2025) · doi:10.1109/gbc60041.2025.11134459

Blockchain and homomorphic encryption based privacy-preserving model aggregation for medical images

Kumar, R., Kumar, J., Khan, A. A., Zakria, Z., Ali, H., Bernard, C. M., Khan, R. U., & Zeng, S. (2022) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2022.102139 · Cited by 66 · see citing works

Blockchain-Federated Deep Neural Network for Privacy-Preserving Healthcare Anomaly Detection

Siddique, M. S., Chauhan, A., & Shukla, D. K. (2026) · CRC Press eBooks · doi:10.1201/9781003743774-138

Blockchain-Augmented Federated Learning for Secure and Healthcare Diagnosis from Distributed Electronic Health Records

Dhanraj, J. A., Dhongle, P., R.Tamilamuthan, M.Lakshmanan, Ashtankar, N., & Hole, S. R. (2026) · International Conference on Emerging Trends in Advancements and Applications of Computational Intelligence Techniques (ETAACT) · doi:10.1109/etaact69135.2026.11541890