Much of the course content will be available through lecture slides and associated bibliographic references.
All the material above is available publicly or through the course page.
Argomenti del programma: Please note that minor changes to the schedule or course content may occur due to instructor commitments or unforeseen circumstances. Any such changes will be communicated to students in a timely manner. - Introduction - Introduction to the course - Machine Learning Fundamentals and Health Applications - Fundamentals of Probability and Statistics for AI - Lab Tutorial 1: Hypothesis testing - Machine Learning:…
Testi d'esame di Artificial Intelligence For Digital Health del prof. Davide Bacciu, canale unico, corso di laurea in Informatics for Digital Health – sede di Pisa (Laurea magistrale (LM-18)), Università di Pisa, 1º anno · 2º semestre · 9 CFU, a.a. 2026/2027. Libri adottati: Jenna Wiens – Patient Risk Stratification with Time-Varying Parameters; Tim Smolem et atl; Ping Wang – ACM Comput; David – Mitchel Klein; Dimitris Bertsimas – Machine learning; Chen – Auto-Encoders in Deep Learning—A Review with New…; Pratella – A Survey of Autoencoder Algorithms to Pave…; Manuel Cossio – A Comprehensive Catalogue of 65 Techniques for…; Pooya Mobadersany – Predicting cancer outcomes from histology and genomics…; Jun ma; Bacciu – A Gentle Introduction to Deep Learning for…; [SD] Simon – Understanding Deep Learning; Aliferis – AI and ML in health Care and….
Libri Universitari