Program Overview

Program Overview

The program is a MOOC (Massive Open Online Course) designed for Bachelor of Science students, focusing on the topic of "Dati in medicina: dalla generazione agli algoritmi di AI" (Data in Medicine: from Generation to AI Algorithms).

Course Description

This course explores the journey of data in medicine, from its physical roots to its transformation and use in the digital world. It covers the acquisition and conversion of real signals into digital data, the principles of digitalization, and the challenges of data quality. The course also introduces the principles of data management, medical standards (DICOM, HL7, FHIR), and the importance of normalization and harmonization.

Learning Outcomes

By actively participating in the course, students will achieve the following learning outcomes:

• Explain the process of acquiring and converting real signals into digital data, linking it to their physical nature.
• Understand the fundamental principles of digitalization (sampling, quantization, physical meaning of values, compression).
• Recognize the challenges related to data quality, including the derivation of categorical data and inter-operator variability.
• Know the principles of data management and medical standards (DICOM, HL7, FHIR) and the importance of normalization/harmonization.
• Recognize the role of digital data in the AI ecosystem in medicine and the ethical implications related to bias.
• Discuss and explain the impact of data quality and preparation on AI algorithm performance through practical examples.

Course Structure

The course consists of several weeks of study, with each week focusing on a specific topic. The course includes:

• Lectures
• Interactive quizzes and self-assessment quizzes
• Practical exercises and guided simulations
• Case study analysis and thematic discussions
• Readings and in-depth studies

Week 2 Overview

Week 2 explores the topic of "Dal segnale fisico al dato digitale: esplorando l'origine, la qualitŕ e la gestione dei dati medici" (From Physical Signal to Digital Data: Exploring the Origin, Quality, and Management of Medical Data). It covers the introduction to Week 2, noise, artifacts, and essential filtering, as well as compression and standards for efficient archiving and transmission.

Assessment and Certification

The course includes an assessment based on quizzes, with unlimited attempts allowed but a 15-minute waiting period between attempts. The course is considered completed if a student achieves at least 60% of the total score in each of the evaluated quizzes. Upon completion, students can obtain an Open Badge, which is not an official certificate and does not grant university credits, grades, or diplomas.

Instructor

The course instructor is Mattia Savardi, a researcher and lecturer at the Department of Medical-Surgical Specialties, Radiological Sciences, and Public Health at the University of Brescia. His research focuses on the use of Artificial Intelligence for the analysis of complex biomedical data.

Course Availability

The course is offered online and is free of charge.