Artificial Intelligence in Medicine

MD Program @ CISMED

Giuseppe Riccardi
Giovanni Iacca
Eleonora Maria Aiello

Simone Alghisi
Massimo Rizzoli
Gabriele Roccabruna

The objectives of this AI curriculum (lectures, labs, and internship@Hospitals) are specifically designed and developed for medicine students: 1) to provide a conceptual mapping of the fundamental principles that govern artificial intelligence systems, 2) to present their applications in medicine and 3) Develop AI use cases in the hospitals' clinical units within interdisciplinary teams.
The lab activities will provide practical examples of the main applications of machine learning in the medical field, particularly focusing on the automatic analysis of data for diagnostic purposes (for example, through automatic image classification). Last but not least, the internship will aim to apply what has been learned in the lectures and the laboratories to real case studies in a clinical environment or research groups in the AI field. The clinical units maybe from all specialties, including neurosurgery, imaging diagnostics, ophthalmology, health physics, cardiology, and endovascular surgery.

The course will present the fundamental concepts of artificial intelligence (AI) systems and machine learning. Case studies and applications of AI systems in the medical and health sector will be discussed. In the central part of the course, laboratory sessions will provide practical examples of analysis of physiological signals. Supervised and unsupervised learning techniques will be presented and applied to these signals. Several examples of automatic diagnostic analysis of time series and images will be provided. The internship will be carried out in one of the operational units of the clinics affiliated with the medical school. The course aims to transfer the knowledge acquired in the lectures and labs to the review of the decision-making processes in the medical and clinical fields.

Final Assessment
The students will present and discuss the use case they have co-developed with MDs and AI researchers during the internship at the hospital's units.

=======Lecture, Lab material============


Introduction (Objectives, Organization and Assessment)
What is AI
Machine Learning Concepts and Frameworks
     Reinforcement Learning
AI for Medicine and Health
     Use Cases

Labs and Internship Organization


Data and Visualization
Logistic Regression
Decision Trees
Unsupervised Learning
Convolutional Neural Networks
Multi-Layer Perceptron Neural Networks
RapidWeaver Icon

Made in RapidWeaver