Applied Generative AI for Health Sciences Research
Applied Generative AI for Health Sciences Research
Welcome
Applied Generative AI for Health Sciences Research
Copyright
Preface
Conventions
How to use this book
Foundations
1
A Brief History of Generative AI: How We Got Here
2
The Generative AI Landscape for Researchers
3
Reasoning Models, Context, and the Verification Problem
Working with Biomedical Knowledge and Data
4
Retrieval-Augmented Generation over Biomedical Corpora
5
Synthetic Data and Privacy-Preserving Generation
6
Multimodal Medical AI for Public Health Tasks
Agentic Workflows and Tool Use
7
Agents, Tool Use, and the Model Context Protocol
8
Deep Research and Evidence Synthesis Pipelines
Evaluation, Safety, and Governance
9
Evaluation Beyond the Benchmark
10
Safety, Bias, and Red-Teaming in Health Contexts
11
Regulation, Privacy, and the IRB
Customisation, Deployment, and Practice
12
Customisation and Adoption: Fine-Tuning, Distillation, and AI-Augmented Teams
13
Deploying AI in Clinical and Public-Health Practice
References
Appendices
Credits
Colophon
Applied Generative AI for Health Sciences Research
Code
A graduate textbook.
Welcome
Copyright