CdSBIOTECHNOLOGIES AND APPLIED ARTIFICIAL INTELLIGENCE FOR HEALTH
Codice551EE
CFU6
PeriodoSecondo semestre
LinguaInglese
| Moduli | Settore/i | Tipo | Ore | Docente/i | |
| MOLECULAR GENETICS AND MOLECULAR MEDICINE IN THE AI-ERA | BIO/18 | LEZIONI | 60 |
|
Students will be provided with robust basis on how machine learning and artificial intelligence approaches are applied to molecular genetics and genomics as well as molecular medicine (diagnostics and precision medicine).
Knowledge will be assessed by oral interview.
Students will acquire the skills to analyze and discuss findings related to applications and approaches of machine learning and artificial intelligence designed to solve genetics/genomics issues and to integrate precision medicine field.
The skills acquired by the students will be assessed by means of oral interviews.
Students will acquire awareness on the potentialities and limitations of AI-based approaches in molecular genetics and molecular medicine. Students will acquire accuracy and precision when discussing experimental data related to artificial intelligence based approaches in molecular genetics and medicine.
Beahviors will be assessed by means a report of exercices and laboratories activities
Genetics and molecular biology, as from the 1st year master's degree or the previous first-level degree of the admitted students.
Each student is invited to verify the pre-requisites on the regulations of the Biotechnologies and Applied Artificial Intelligence for Health master's degree. Every examination taken without considering pre-requisites is considered as null (UNIPI regulation, art. 24.3)
Classroom lessons, seminars, discussion of research findings
The course is intended to provide students with information on how machine learning and artificial intelligence approaches are applied to molecular genetics and genomics as well as molecular medicine (diagnostics and precision medicine). Several applications will be discussed and, for each application, the following scheme will be followed: description and contextualization of the disease / pathologic condition / biotechnology problem; available (still insufficient or limited) solutions; AI approaches.
Reviews and selected papers will be discussed and provided to the students via the dedicated MS Teams platform of the course
The course will be in person, but lessons will be video-recorded and the corresponding video files will be made available for participating students. All the students interested in the course must have sent an email to Prof. Giovannoni (roberto.giovannoni@unipi.it) with the indication of the following information: master's degree, year of the course, motivation to attend the course
Oral interview and a laboratory activity report (to be also discussed during the interview)
Examination Committee
President: Prof. Roberto Giovannoni
Member: Prof. Enrica Strettoi