Who / When / Where
Instructor: Zhiyu Wan
Teaching Assistant: Jiarui Xu, Haoyun Xu
Semester: Fall 2026
Time: Wednesdays, 15:00-16:40
Location: School of Information Science and Technology, Room 1D106
Office Hours: Upon request, Location: BME Building, Room 228
Schedule
(Note: This schedule is tentative and subject to change.)
| Week | Chapter | Teaching Contents | Readings | Assignments |
| Week 1, Wednesday Sept 16, 15:00-16:40 Lecture 1 (PDF) | I. Course Introduction and Overview of Data Privacy and Ethics | Course introduction. The role of medical data in the age of AI. Concept of data privacy and its importance. Concept of ethics and morality and their importance. | / | / |
| Week 2, Wednesday Sept 24, 15:00-16:40 Lecture 2 (PDF) | II. Ethical Issues in Life Sciences, Medicine, and Informatics (a) | AI ethics: machine morality and ethics, automation, and employment. | (Optional: 1.《信息科学技术伦理与道德》Chs.8-10. 3.《信息科学技术伦理与道德》Chs.3&4.) | |
| Week 3, Wednesday Sept 30, 15:00-16:40 Lecture 3 (PDF) | II. Ethical Issues in Life Sciences, Medicine, and Informatics (b) | Research ethics: ethical guidelines for human and animal experiments and scientific research. Life sciences ethics: controversies arising from reproductive technology, genetic technology, stem cell research, etc. Information security and privacy issues: personal data breaches, surveillance technology, facial recognition. | (Optional: 1.《工程伦理》Chs.10&12. 2.《信息科学技术伦理与道德》Chs.5. 3. Price WN, Cohen IG. Privacy in the age of medical big data. Nature medicine. 2019 Jan;25(1):37-43. 4. S. Warren and L. Brandeis. The right to privacy. Harvard Law Review. 1890. http://faculty.uml.edu/sgallagher/Brandeisprivacy.htm) | |
| Week 4, Saturday Oct 10, 15:00-16:40 Lecture 4 (PDF) | III. Ethical Issues in Life Sciences, Medicine, and Informatics (c) + Ethical Issues in Data Sharing and Medical AI (a) | Medical ethics issues: abortion, euthanasia, public health issues, and medical ethics concerning special populations (infants, adolescents, psychiatric patients, etc.). Data governance and data lifecycle management. Importance of biomedical data sharing and privacy challenges. | ||
| Week 5, Wednesday Oct 14, 15:00-16:40 Lecture 5 (PDF) | III. Ethical Issues in Data Sharing and Medical AI (b) | In-class quiz 1. Algorithmic fairness and bias issues in medical AI. | (Optional: 1. Dunkelau J, Leuschel M. Fairness-aware machine learning: An extensive overview. 2019. https://stups.hhu-hosting.de/downloads/pdf/fairness-survey.pdf) 2. Xu J, Xiao Y, Wang WH, Ning Y, Shenkman EA, Bian J, Wang F. Algorithmic fairness in computational medicine. EBioMedicine. 2022 Oct 1;84. https://www.thelancet.com/pdfs/journals/ebiom/PIIS2352-3964(22)00432-7.pdf) | |
| Week 6, Wednesday Oct 21, 15:00-16:40 Lecture 6 (PDF) | III. Ethical Issues in Data Sharing and Medical AI (c) | Transparency and interpretability in medical AI. | (Optional: 1. Molnar, Christoph. Interpretable machine learning. 2020. (Ch. 5) https://christophm.github.io/interpretable-ml-book/ 2. Lundberg, S. M., & Lee, S. I. A unified approach to interpreting model predictions. NeurIPS. 2017 (Original SHAP paper).) | |
| Week 7, Wednesday Oct 28, 15:00-16:40 Lecture 7 (PDF) | IV. Legal and Regulatory Frameworks | The impact of international laws and regulations like HIPAA and GDPR on biomedical data. China’s data security law and personal information protection law. Compliance requirements for medical data sharing. | (Optional: 1. Gruschka N, Mavroeidis V, Vishi K, Jensen M. Privacy issues and data protection in big data: a case study analysis under GDPR. In 2018 IEEE international conference on big data (big data) 2018 Dec 10 (pp. 5027-5033). IEEE. 2. 《信息科学技术伦理与道德》Ch.5.2.) | |
| Week 8, Wednesday Nov 4, 15:00-16:40 Lecture 8 (PDF) | V. Privacy Risks & Common Privacy Protections of Biomedical Data (a) | In-class quiz 2. Privacy risks of electronic health records. Main attack models: re-identification attacks. Privacy risk assessment methods. | ||
| Week 9, Wednesday Nov 11, 15:00-16:40 Lecture 9 (PDF) | V. Privacy Risks & Common Privacy Protections of Biomedical Data (b) | Introduction to Genomic sequencing and Genome-Wide Association Study (Guest Lecturer) | ||
| Week 10, Wednesday Nov 18, 15:00-16:40 Lecture 10 (PDF) | V. Privacy Risks & Common Privacy Protections of Biomedical Data (c) | Classic data privacy protection techniques: pseudonymization, K-anonymization, and others. Announce course project topics. | HW #1 Posted. | |
| Week 11, Wednesday Nov 25, 15:00-16:40 Lecture 11 (PDF) | V. Privacy Risks & Common Privacy Protections of Biomedical Data (d) | Sharing and privacy risks of genomic data. Main attack models: membership inference attacks, and reconstruction attacks. Complete team formation. | ||
| Week 12, Wednesday Dec 2, 15:00-16:40 Lecture 12 (PDF) | V. Privacy Risks & Common Privacy Protections of Biomedical Data (e) | Basics of game theory. Game-theoretic models for optimized privacy protection. | ||
| Week 13, Wednesday Dec 9, 15:00-16:40 Lecture 13 (PDF) | VI. Advanced Privacy Protections of Biomedical Data (a) | Basics of cryptography. Methods and applications of homomorphic encryption technologies for privacy-preserving computing in medicine. Methods and applications of secure multi-party computation technologies for privacy-preserving computing in medicine. Methods and applications of encrypted hardware technologies for privacy-preserving computing in medicine. Basic principles and applications of differential privacy. Complete project topic selection. | HW #1 Due. HW #2 Posted. | |
| Week 14, Wednesday Dec 16, 15:00-16:40 Lecture 14 (PDF) | VI. Advanced Privacy Protections of Biomedical Data (b) | Presentations of team project proposals. Methods and applications of federated learning models in privacy protection. Methods and applications of synthetic data generation techniques in privacy protection. | Project Proposal Presentation and Report Due at 23:59 on Dec 15. | |
| Week 15, Wednesday Dec 23, 15:00-16:40 Lecture 15 (PDF) | VII. Privacy and Ethical Issues in Cutting-Edge AI Technologies for Healthcare | Basics of large language models and generative AI. Applications of large language models and generative AI in medicine. Privacy risk issues of large language models and generative AI. Fairness issues of large language models and generative AI. Other ethical issues of large language models and generative AI. Solutions to ethical issues of large language models and generative AI and future directions. | ||
| Week 16, Wednesday Dec 30, 15:00-16:40 | VIII. Course Project Presentation | Group presentations (oral + poster) and feedback. | Final Project Presentation Due at 23:59 on Dec 26. HW #2 Due at 15:00 on Jan 7. Final Project Report (Research Paper) Due at 23:59 on Jan 9. |
