Medicine and Surgery HT

Applications of artificial intelligence in medicine: for diagnosis, prognosis, prediction, therapy. Sources of big data of healthcare interest: electronic medical records, administrative data, hospital discharge forms, -omics technologies (genomics, transcriptomics, proteomics, multiomics) Digital Health and e-Health as "efficient and secure use of information and communication technologies to support health and health-related sectors, including health care, health surveillance and health education, knowledge and research". Wearable devices and the "Internet-of-things". Data sharing and security. The contribution of big data and artificial intelligence to precision medicine and the medicine of the four Ps (preventive, predictive, personalized and participatory). Potential limitations: overfitting, spurious correlations, "black boxes"

Basic knowledge of IT and database management; knowledge of basic clinical methodology which is provided in the same semester.

Materials on the University Moodle platform.

Compulsory attendance, with assessment carried out on the occasion of each individual activity by the responsible teacher. The obligation to attend is considered fulfilled when 75% of attendance is reached.

Since this is an Integrated Course, the learning assessment will be carried out in a unitary and integrated manner by all teachers; the single module assesment will include completing a multiple choice questionnaire (at least 18 correct answers out of 30 questions are required to pass).

The teacher delivers lectures with traditional methods with audiovisual aids and scheduling of lessons as reported on GOMP Aure/Orari system, published on the website of the course.