B6268 - BASIC OF ARTIFICIAL INTELLIGENCE AND APPLICATON IN MEDICINE

Learning outcomes

At the end of this course students will

•reach an adequate degree of awareness of AI systems to make them responsible users of AI-based tools as future doctors;

• be able to critically evaluate the main references of the EU legal and ethics framework fostering human centered AI

• know the main neuronal networks architecture and learning rules (supervised, unsupervised, semi-supervised and reinforcement learning);

• know the main application of AI to selected medical examples (histopathological and medical imaging and genomics) by using user-friendly coding environment (Pytorch, Keras, etc.).

• acquire the basic knowledge of the application of artificial intelligence, machine learning and deep learning to medical devices for the diagnosis and treatment of patient in compliance with current regulations.

Course contents

0. Introduction to AI in medicine

1. Supervised, unsupervised and semi-supervised learning rules

2. Neural networks and Deep learning

3. Development environments

4. Privacy and ethics of medical data

5. Applications to selected medical problems

Readings/Bibliography

Lecture notes and selected articles

Teaching methods

Lectures and PC practical activity

Assessment methods

Short research project and article reading

Teaching tools

Slides of the lessons and software distributed, or made available to students via github

Office hours

See the website of Gastone Castellani