Part I. Artificial Intelligence. basic concepts and definitions 1. Machine Learning and Deep Learning 2. Artificial Neural Networks 3. Data Mining and Data Science Part II. Artificial Intelligence. deep learning and generative AI 4.

Transformers 5. Bidirectional Encoder Representations from Transformers (BERT) 6. Generative AI, Large Language Models 7. GPT. Generative Pre-trained Transformers 8. BARD Part III. Artificial Intelligence in Biomedical Research 9. Bioinformatics methods and AI.

10. Network Science methods and AI 11. AI for investigating the molecular basis of diseases. 12. AI and Drug Repurposing Part IV. Artificial Intelligence in Clinical Practice 13. AI based analysis of biosignals 14. AI-based analysis of bioimages 15.

AI-based analysis of Medical Reports and Electronic Health Records 16. AI in surgery 17. AI in oncology Part V. Artificial Intelligence in Public Health 18. One-Health AI 19. Virus diffusion prevention and management Part VI. 20. Opportunities and Risks of Generative AI (GPT) in Medicine 21.

Bias 22. Clinician and Dataset Shift 23. Explainability and Black Box models 24. Privacy and Security 25. Legal and ethical aspects 26. Integrating human and AI knowledge.