| Title | Authors | Year | Journal |
| A Framework for Adaptive Differential Privacy | Daniel Winograd-Cort et al. | 2017 | Proceedings of the ACM on Programming Languages |
| *A fully homomorphic encryption based on magic number fragmentation and El-Gamal encryption: Smart healthcare use case | Mostefa Kara et al. | 2021 | Expert Systems |
| *An Adaptive Differential Privacy Algorithm for Range Queries over Healthcare Data | Asma Alnemari et al. | 2017 | 2017 IEEE International Conference on Healthcare Informatics (ICHI) |
| *Applying Secure Multi-Party Computation to Improve Collaboration in Healthcare Cloud | Mbarek Marwan et al. | 2016 | 2016 Third International Conference on Systems of Collaboration (SysCo) |
| A Statistical Framework for Differential Privacy | Larry Wasserman & Shuheng Zhou | 2010 | Journal of the American Statistical Association |
| A Survey on Homomorphic Encryption Schemes: Theory and Implementation | Abbas Acar et al. | 2018 | ACM Computing Surveys |
| *Cloud-based Secure Health Monitoring: Optimizing Fully-Homomorphic Encryption for Streaming Algorithms | Alex Page et al. | 2014 | 2014 IEEE Globecom Workshops (GC Wkshps) |
| Deep Learning with Differential Privacy | Martín Abadi et al | 2016 | Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security |
| *Differential Privacy for Clinical Trial Data: Preliminary Evaluations | Duy Vu & Aleksandra Slavković | 2009 | 2009 IEEE International Conference on Data Mining Workshops |
| Differential Privacy Preservation for Deep Auto-Encoders: An Application of Human Behavior Prediction | NhatHai Phan et al. | 2016 | Proceedings of the AAAI Conference on Artificial Intelligence |
| dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning | Han Cao et al. | 2022 | Bioinformatics |
| Emerging technologies towards enhancing privacy in genomic data sharing | Bonnie Berger and Hyunghoon Cho | 2019 | Genome Biology |
| Federated learning and differential privacy for medical image analysis | Mohammed Adnan et al. | 2022 | Scientific Reports |
| *Federated machine learning in data-protection-compliant research | Alissa Brauneck et al. | 2023 | Nature Machine Intelligence |
| Flimma: a federated and privacy-aware tool for differential gene expression analysis | Olga Zolotareva et al. | 2021 | Genome Biology |
| Gaussian differential privacy | Jinshuo Dong et al. | 2022 | Journal of the Royal Statistical Society Series B: Statistical Methodology |
| Mechanisms for Hiding Sensitive Genotypes With Information-Theoretic Privacy | Fangwei Ye et al. | 2022 | IEEE Transactions on Information Theory |
| Privacy-Preserving Artificial Intelligence Techniques in Biomedicine | Reihaneh Torkzadehmahani et al. | 2022 | Methods of Information in Medicine |
| Privacy-preserving genotype imputation in a trusted execution environment | Natnatee Dokmai et al. | 2021 | Cell Systems |
| Secure human action recognition by encrypted neural network inference | Miran Kim et al. | 2022 | Nature Communications |
| Sequre: a high‑performance framework for secure multiparty computation enables biomedical data sharing | Haris Smajlović et al. | 2023 | Genome Biology |
| Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption | David Froelicher et al. | 2021 | Nature Communications |