Thematic Course:
Artificial Intelligence for Medicine
Date
14 & 18, 19 May 2026
Organizer
Davide La Torre (UNIBO)
Location
IEO Campus, Via Adamello 16 - Milan
About the Course
This course introduces basic concepts of artificial intelligence and machine learning and their applications to the field of medicine. Students will explore various AI methods and technologies used for data analysis, medical diagnosis, treatment planning, and healthcare management. The course will introduce fundamental concepts, algorithms, and real-world applications.
The course includes a final project requiring approximately 5 hours of individual work, where students will apply course concepts to a medical AI use case.
Lessons location: Gold Room, bld. 13
14:30-16:30
Foundations of AI in Medicine
– Introduction to Artificial Intelligence
– Overview of Machine Learning
– Supervised, Unsupervised, and Reinforcement Learning
– Applications in diagnosis, prognosis, treatment selection, and drug discovery
– Regulatory and ethical considerations
– Explainable AI (XAI) in healthcare
Lessons location: Conference Room, bld. 9
9:30-12:30
Machine Learning and Deep Learning in Healthcare
– Machine Learning fundamentals
– Evaluation metrics for medical AI models
– Introduction to Deep Learning
– Neural Networks and Convolutional Neural Networks (CNNs)
– Applications in medical imaging
– Limitations, bias, and interpretability challenges
13:30-17:30
Privacy-Preserving and Distributed AI
– Data challenges in healthcare
– Introduction to Federated Learning
– Centralized vs distributed learning approaches
– Use cases in multi-hospital collaborations
– Technical and ethical challenges
Lessons location: Silver Room, bld. 13
9:30-12:30
Practical AI with Orange & AI-Assisted Python
– Introduction to Orange Data Mining
– Data preprocessing and feature engineering
– Model building and evaluation using Orange
– Introduction to Python using ChatGPT
– Generating and validating AI-assisted code for medical datasets
– Responsible use of AI coding tools
13:30-17:30
AI Agents and Large Language Models in Medicine
– AI Agents and Agentic AI concepts
– Autonomous and semi-autonomous clinical systems
– Applications of LLMs in medicine
– Clinical text analysis and NLP basics
– Designing simple AI agent workflows for healthcare
– Risks, safety, and governance
Final project may include:
– Development of a machine learning workflow using Orange
– Design of an AI agent concept for a healthcare scenario
– Evaluation of a medical AI model
– Proposal for a federated learning application
– Critical analysis of an AI system in medicine
Projects must demonstrate:
– Understanding of AI methodologies
– Critical evaluation of risks and ethics
– Practical application of tools covered in the course