A survey on differential privacy for medical data analysis

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Internet of Things, Real-Time Decision Making, and Artificial Intelligence

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Federated Learning and Differential Privacy for Medical Image Analysis

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iPrivacy: Image Privacy Protection by Identifying Sensitive Objects via Deep Multi-Task Learning

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Differentially Private Model Publishing for Deep Learning

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Evaluating Differentially Private Machine Learning in Practice

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Privacy in the Genomic Era

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Security and Privacy Analysis of Mobile Health Applications: The Alarming State of Practice

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DeepRank-GNN: a graph neural network framework to learn patterns in protein–protein interfaces

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Privacy-preserving data exploration in genome-wide association studies

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Medical imaging deep learning with differential privacy

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What are the underlying transmission patterns of COVID-19 outbreak? An age-specific social contact characterization

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Locally Private Graph Neural Networks

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Scalable privacy-preserving data sharing methodology for genome-wide association studies

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PPM-HDA: Privacy-Preserving and Multifunctional Health Data Aggregation With Fault Tolerance

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Privacy-Preserved Electronic Medical Record Exchanging and Sharing: A Blockchain-Based Smart Healthcare System

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A Comprehensive Survey on Local Differential Privacy toward Data Statistics and Analysis

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Tempered Sigmoid Activations for Deep Learning with Differential Privacy

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A Critical Review on the Use (and Misuse) of Differential Privacy in Machine Learning

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NPI-GNN: Predicting ncRNA–protein interactions with deep graph neural networks

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Distributed Memetic Algorithm for Outsourced Database Fragmentation

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Differential Privacy with Bounded Priors

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MDDE: multitasking distributed differential evolution for privacy-preserving database fragmentation

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Differential privacy for eye tracking with temporal correlations

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Differential Privacy Protection Against Membership Inference Attack on Machine Learning for Genomic Data

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Drug Package Recommendation via Interaction-aware Graph Induction

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Privacy-CNH: A Framework to Detect Photo Privacy with Convolutional Neural Network using Hierarchical Features

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Differential Privacy for Data and Model Publishing of Medical Data

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Privacy-preserving aggregation of personal health data streams

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HGNAS++: Efficient Architecture Search for Heterogeneous Graph Neural Networks

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A differential privacy protection scheme for sensitive big data in body sensor networks

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Culture versus Policy: More Global Collaboration to Effectively Combat COVID-19

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Differential privacy under dependent tuples—the case of genomic privacy

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GraphNAS++: Distributed Architecture Search for Graph Neural Networks

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Federated Learning with Gaussian Differential Privacy

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Reconciling Utility with Privacy in Genomics

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Local differential privacy protection for wearable device data

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Inference attacks against differentially private query results from genomic datasets including dependent tuples

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Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation

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Improving Deep Learning with Differential Privacy using Gradient Encoding and DenoisingPreprint

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Genomic Data Sharing under Dependent Local Differential Privacy

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Knowledge transfer-based distributed differential evolution for dynamic database fragmentation

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Differential privacy medical data publishing method based on attribute correlation

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An Information-Driven Genetic Algorithm for Privacy-Preserving Data Publishing

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DSGA: A Distributed Segment-Based Genetic Algorithm for Multi-Objective Outsourced Database Partitioning

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Privacy and Security in the Genomic Era

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Privacy-Preserving Deep Inference for Rich User Data on The CloudPreprint

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Collaborative Deep Learning for Medical Image Analysis with Differential Privacy

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Privacy-Preserving mHealth Data Release with Pattern Consistency

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Achieving differential privacy of genomic data releasing via belief propagation

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DP-QIC: A differential privacy scheme based on quasi-identifier classification for big data publication

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Patient Privacy in the Genomic Era

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What Country, University, or Research Institute, Performed the Best on Covid-19 During the First Wave of the Pandemic?

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Privacy preservation in big data: a survey

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Addressing the Threats of Inference Attacks on Traits and Genotypes from Individual Genomic Data

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Data Analysis of COVID-19 Hospital Records Using Contextual Patient Classification System

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Research on Differential Privacy for Medical Health Big Data Processing

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Heterogeneous Graph Neural Network for Privacy-Preserving RecommendationPreprint

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Federated learning for anomaly detection on Internet of Medical Things: A survey

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Human-centred artificial intelligence for mobile health sensing: challenges and opportunities

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Differential privacy for medical deep learning: methods, tradeoffs, and deployment implications

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Can Synthetic Data be Fair and Private? A Comparative Study of Synthetic Data Generation and Fairness Algorithms

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Advancing privacy in learning analytics using differential privacy

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Privacy-Preserving in Medical Image Analysis: A Review of Methods and Applications

Zhu, Y., Yin, X., Liew, A. W., & Tian, H. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-4207-6_15 · Cited by 20 · see citing works

Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare

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An automated privacy-preserving self-supervised classification of COVID-19 from lung CT scan images minimizing the requirements of large data annotation

Chowa, S. S., Bhuiyan, M. R. I., Tahosin, M. S., Karim, A., Montaha, S., Hassan, M. M., Shah, M. A., & Azam, S. (2025) · Scientific Reports · doi:10.1038/s41598-024-83972-6 · Cited by 15 · see citing works

DeepSeek-Inspired Exploration of RL-Based LLMs and Synergy with Wireless Networks: A Survey

Qiao, Y., Tran, P.-N., Yoon, J. S., Nguyen, L. X., Huh, E., Niyato, D. T., & Hong, C. S. (2025) · ACM Computing Surveys · doi:10.1145/3776745 · Cited by 19 · see citing works

Optimization of Privacy-Utility Trade-Off for Efficient Feature Selection of Secure Internet of Things

Kil, Y.-S., Lee, Y.-J., Jeon, S.-E., Oh, Y.-S., & Lee, I.-G. (2024) · IEEE Access · doi:10.1109/access.2024.3467049 · Cited by 13 · see citing works

Application of Federated Learning in Cardiology: Key Challenges and Potential Solutions

Rahman, S., Karmarkar, C., & Islam, S. M. S. (2024) · Mayo Clinic Proceedings Digital Health · doi:10.1016/j.mcpdig.2024.09.005 · Cited by 12 · see citing works

Computational modeling for medical data: From data collection to knowledge discovery

Yin, Y., Xu, S., Hong, Y., Cai, Y., Tang, W., Wang, J., Shen, B., Zong, H., & Yu, G. (2024) · The Innovation Life · doi:10.59717/j.xinn-life.2024.100079 · Cited by 11 · see citing works

Differential Privacy Configurations in the Real World: A Comparative Analysis

Khavkin, M., & Toch, E. (2025) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2025.3603731 · Cited by 11 · see citing works

A Review on Integrating Breast Cancer Clinical Data: A Unified Platform Perspective

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Artificial intelligence‐assisted theranostics for brain tumors: Advancements and future perspectives

Li, M., Zhang, L., Ullah, Z., Zhang, Y., Wei, S., Huang, L., & Guo, B. (2025) · Open Research (University of Surrey) · doi:10.1002/viw.20250119 · Cited by 8 · see citing works

The future of multimorbidity management in the older adults: transforming AI-enabled precision medicine

Deng, W., Zhang, L., Yue, J.-R., & Huang, X.-L. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1691682 · Cited by 9 · see citing works

A Theoretical Comparison of Federated Learning with Differential Privacy and Blockchain for Security and Privacy in IoMT

Farooqi, S. A., Rahman, A. B. A., & Saad, A. B. (2025) · International Conference on Ubiquitous Information Management and Communication (IMCOM) · doi:10.1109/imcom64595.2025.10857505 · Cited by 6 · see citing works

Refining medical large language models: key insights from instruction tuning

Alqahtani, M. Q., Al-Barakati, A. A., & Alotaibi, F. S. (2025) · PeerJ Computer Science · doi:10.7717/peerj-cs.3216 · Cited by 6 · see citing works

Randomized Response and Differential Privacy

Ioannidis, A., Λίτκε, Α., & Papadakis, N. K. (2024) · International Conference on PErvasive Technologies Related to Assistive Environments (PETRA) · doi:10.1145/3652037.3663902 · Cited by 4 · see citing works

ShieldDFL: A Blockchain-Based Federated Learning Framework With Dual Privacy Protection and Reputation-Driven Consensus

Cai, Y., Du, X., Zhang, C., & Li, M. (2025) · IEEE Access · doi:10.1109/access.2025.3576261 · Cited by 4 · see citing works

The Convergence of IoT, ML, and Big Data in Self-Service Innovation

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A Review on Fuzzy Cognitive Mapping: Recent Advances and Algorithms

Nápoles, G., Jastrzębska, A., Grau, I., Salgueiro, Y., & León, M. (2026) · Big Data and Cognitive Computing · doi:10.3390/bdcc10010022 · Cited by 3 · see citing works

A Randomized Response Framework to Achieve Differential Privacy in Medical Data

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Application of the joint clustering algorithm based on Gaussian kernels and differential privacy in lung cancer identification

Hang, Y., Hai-xia, Z., Yang, M., Wang, N., Kong, M., & Zhao, M. (2025) · Scientific Reports · doi:10.1038/s41598-025-01873-8 · Cited by 3 · see citing works

UdpTrace: Utility-enhanced differential privacy scheme for trajectory data publishing

Sun, W., Zhao, K., Liang, G., Liang, Z., & Jiang, L. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.130785 · Cited by 3 · see citing works

Enhance differential privacy mechanisms for clinical data analysis using CNNs and reinforcement learning

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Preserving Medical Data with Renyi Differential Privacy

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Distributed empirical likelihood inference with privacy guarantees

Liu, Q., & Li, Z. (2025) · Statistics and Computing · doi:10.1007/s11222-025-10614-w · Cited by 2 · see citing works

Frequency estimation under relaxed input-discriminative local differential privacy

Kuang, X., Zhu, Y., Liu, R., & Zhang, S. (2025) · Information Sciences · doi:10.1016/j.ins.2025.122351 · Cited by 2 · see citing works

Exploring differential privacy in CNNs, LSTMs, GRUs, and RNNs for heartbeat detection from multimodal data

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The role of Anonymization Techniques in Differential Privacy

Vardalachakis, M., & Kalloniatis, C. (2025) · International Conference on Computer Technology Applications (ICCTA) · doi:10.1109/iccta65425.2025.11166256 · Cited by 2 · see citing works

Differentially Private Selection using Smooth Sensitivity

Yamamoto, A., & Shibuya, T. (2024) · IEEE International Performance, Computing, and Communications Conference · doi:10.1109/ipccc59868.2024.10850477 · Cited by 2 · see citing works

Challenges and future directions of AIRR-seq-based diagnostics

Stervbo, U., Filippidis, P., Breden, F. J., Cowell, L. G., Davi, F., Greiff, V., Langerak, A. W., Prak, E. T. L., Sharland, A. F., Miho, E., et al. (2025) · ImmunoInformatics · doi:10.1016/j.immuno.2025.100056 · Cited by 2 · see citing works

Direction-Oriented Smooth Sensitivity and Its Application to Genomic Statistical Analysis

Yamamoto, A., & Shibuya, T. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-9101-2_4 · Cited by 1 · see citing works

Cryptographic Commitments on Anonymizable Data

Bultel, X., Chevalier, C., Jojon, C., Liu, D., & Nguyen, B. (2025) · IEEE European Symposium on Security and Privacy · doi:10.1109/eurosp63326.2025.00037 · Cited by 1 · see citing works

Artificial Intelligence (AI) in Patient–Healthcare Relationships: Psychosocial Perspective

Saikia, M. J., & Borthakur, D. (2025) · IEEE Access · doi:10.1109/access.2025.3611818 · Cited by 1 · see citing works

Between Privacy and Utility: Navigating Inference Risks in De-Identified Health Data

Kar, S., Chinthala, L. K., Mohammed, A., Davis, R. L., & Sakib, S. K. (2025) · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...) · doi:10.1109/bhi67747.2025.11269493 · Cited by 1 · see citing works

Advancements and Challenges in Federated Learning for Privacy-Preserving Smart Healthcare: A Review

Rimi, H. A., Asaduzzaman, M., Bhuiyan, M. J. U., Shoaib, H. A., Fuad, K. M. N. R., & Rahman, M. A. (2025) · Studies in computational intelligence · doi:10.1007/978-981-96-8353-6_11 · Cited by 2 · see citing works

A Framework for Operationalizing Cooperative Principles in Data Governance

Mendonça, F., Serugendo, G. D. M., & Abdennadher, N. (2025) · International Conference on Internet of Things: Systems, Management and Security (IOTSMS) · doi:10.1109/iotsms68530.2025.11408547 · Cited by 1 · see citing works

Cybersecurity Challenges, Best Practices, and Future Work in Healthcare

Sharma, D. P., Lashkari, A. H., & Parizadeh, M. (2024) · Progress in IS · doi:10.1007/978-3-031-68034-2_10 · Cited by 1 · see citing works

Adaptive Thermal History De-Identification for Privacy-Preserving Data Sharing of Directed Energy Deposition Processes

Bappy, M. M., Fullington, D., Bian, L., & Tian, W. (2024) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4067210 · Cited by 1 · see citing works

DP ‐ CDA : An Algorithm for Enhanced Privacy Preservation in Dataset Synthesis Through Randomized Mixing

Saha, U., Tonoy, T. M., & Imtiaz, H. (2026) · Security and Privacy · doi:10.1002/spy2.70207 · Cited by 1 · see citing works

Readmission rate prediction using differential privacy technology and multilayer perceptron

Deng, Z., & Jiang, Y. (2024) · International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT) · doi:10.1117/12.3031018

Ensuring Data Privacy in Teen and Children Mental Health Analytics: The Role of Differential Privacy in Data Engineering

Kumar, S. (2024) · International Journal of Scientific Research in Computer Science Engineering and Information Technology · doi:10.32628/cseit241061163

An improved differential privacy-preserving technique for educational dataset

Nisha, N., Singhal, A., & Muttoo, S. K. (2025) · International Journal of Systems Assurance Engineering and Management · doi:10.1007/s13198-025-02766-9

Privacy Playground: A Framework for Assessment of Data Anonymization Methods

John, B., Mahmoud, M., Sarrafzadeh, A., & Patooghy, A. (2025) · IEEE International Conference on Joint Cloud Computing (JCC) · doi:10.1109/jcc67032.2025.00015

Reidentification risks in distributed differentially private data leveraging large language models

Sei, Y., Okumura, H., Ohsuga, A., & Imoize, A. L. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-34109-0.00007-3

Toward Resilient Networks: AI and Deep Learning Strategies for Intrusion Detection

Marthalia, L. (2025) · Digitus Journal of Computer Science Applications · doi:10.61978/digitus.v3i2.881

Biomedical Data Preprocessing

Kazi, J. U. (2025) · Springer eBooks · doi:10.1007/978-3-031-85600-6_4

BioDH: A reversible data hiding framework for secure hiding sensitive data in biological dataPreprint

Zhang, Y., Lin, Y., Haozhe, D., & teng, F. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.28.685003

A quantitative and qualitative assessment of differential privacy’s ability to support collaborative research using a real-world data analysis

Gieser, D. P., Arya, A. R., Smith, R. L., Vozenilek, J. A., Raman, V., & Handler, J. A. (2025) · JAMIA Open · doi:10.1093/jamiaopen/ooaf144

Research on a Blockchain Adaptive Differential Privacy Mechanism for Medical Data Protection

Feier, W., & Rongzuo, G. (2025) · Future Internet · doi:10.3390/fi17120539

Measuring Privacy Risks for Data Asset Management

Li, Y., Wang, T., & Zhang, R. (2025) · Lecture notes in computer science · doi:10.1007/978-981-95-4861-3_36

Differential Privacy and Homomorphic Encryption in Healthcare Artificial Intelligence

Shafik, W., Tufail, A., Silva, L. C. D., & Apong, R. A. A. H. M. (2026) · Studies in computational intelligence · doi:10.1007/978-3-032-03985-9_8

Cross-Silo Prediction of Hospital Readmissions using a Federated Learning Framework

Ayyadurai, M., Anand, M., & Eniyan, P. (2025) · International Conference on Evolutionary Computing and Mobile Sustainable Networks (ICECMSN) · doi:10.1109/icecmsn68058.2025.11383090

Differentially Private Mechanisms Using Enhanced Direction-Oriented Smooth Sensitivity

Yamamoto, A., & Shibuya, T. (2026) · IEEE Annual Computing and Communication Workshop and Conference (CCWC) · doi:10.1109/ccwc67433.2026.11393770

Using personal data in AI model training under EU law

Olifirenko, A. A. (2026) · Digital Law Journal · doi:10.38044/2686-9136-2025-6-12

Privacy-Preserving Clustering via Selective Knowledge Distillation

Luo, J., Qi, X., & Wang, H. (2025) · International Academic Exchange Conference on Science and Technology Innovation (IAECST) · doi:10.1109/iaecst68792.2025.11415255

Reallocation of privacy harm by privacy-preserving machine learning techniques

Goswami, A. (2026) · AI and Ethics · doi:10.1007/s43681-026-01139-7

Optimal Privacy Budget Allocation Framework for Medical Data Publishing

Jahan, S., Hong, W., Ge, Y.-F., Wang, H., Kabir, E., & Whittaker, F. (2026) · Lecture notes in computer science · doi:10.1007/978-981-95-6304-3_10

Blockchain Enabled EHR Sharing with Zero-Trust Access Controls and Differential Privacy Protection

Venkatesan, C., Ananth, J. P., Sharavana, K., Vijayan, V. B., Kumarganesh, S., & Nithya, C. (2026) · International Conference on Innovations in Emerging Technologies for Sustainable Development (ICIETSD) · doi:10.1109/icietsd68684.2026.11584847

Privacy-preserving AI in healthcare: a comprehensive survey of techniques and challenges

Bejaoui, C., Hadded, M., Ghazzai, H., Khalil, O. K., Touati, H., & Laouiti, A. (2026) · Cluster Computing · doi:10.1007/s10586-026-06284-6

Legal analysis of the nature of synthetic data: Personal data, anonymous data, or a sui generis category?

Francia, O. A. A., Núñez-del-Prado, M., Alatrista-Salas, H., & Alvarado, J. G. R. (2026) · Computer law & security review · doi:10.1016/j.clsr.2026.106379

Clinicians are using AI scribes, but what happens to your medical data?

Cullen, A. C. (2026) · doi:10.64628/aa.vayanevhn

HDP-FL: A Hierarchical Differential Privacy Framework for Federated Learning in Healthcare

Dan, Y., Yin, P., Yang, Y., He, Y., Yang, Y., Yang, D., & Li, X. (2026) · International Conference on Computer Science and Blockchain (CCSB) · doi:10.1109/ccsb71176.2026.11716527

Data sparsity in pervasive computing and human–machine interaction: a survey of sources, structures, and remedies

Shen, Y., Liu, Y., Dong, C., Pal, S., Yang, Y., & Shen, J. (2026) · CCF Transactions on Pervasive Computing and Interaction · doi:10.1007/s42486-026-00277-5

A Survey of Privacy Preserving Methods based on Differential Privacy for Medical Data

Yan, H., Yin, M., Yan, C., & Liang, W. (2024) · World Conference on Computing and Communication Technologies (WCCCT) · doi:10.1109/wccct60665.2024.10541778 · Cited by 8 · see citing works

Research on medical data protection based on differential privacy

Yang, Y., shi, J., & wang, S. (2022) · International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA) · doi:10.1117/12.2642608

Chapter 9 Differential Privacy and Medical Data Analysis

Suriyakumar, V. M., Papernot, N., & Goldenberg, A. (2025) · Emerald Group Publishing Limited eBooks · doi:10.1561/9781638284772.ch9

Research on Differential Privacy for Medical Health Big Data Processing

Hu, Y., Ge, L., Zhang, G., & Qin, D. (2019) · International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT) · doi:10.1109/pdcat46702.2019.00036 · Cited by 4 · see citing works

Differential Privacy for Medical Data Analysis

Misra, G., Hazela, B., Chaurasia, B. K., Anurag, & Singh, A. (2026) · IEEE Madhya Pradesh Section Conference (MPCON) · doi:10.1109/mpcon69668.2026.11508248