ARTIFICIAL INTELLIGENCE FOR THE MORPHOLOGICAL CHARACTERIZATION OF CELLS AND TISSUES
cod. 1011048

Academic year 2024/25
1° year of course - First semester
Professor
Carlo GALLI
Academic discipline
Istologia (BIO/17)
Field
A scelta dello studente
Type of training activity
Student's choice
10 hours
of face-to-face activities
1 credits
hub: PIACENZA
course unit
in ENGLISH

Learning objectives

The course aims to provide the learner with the basic concepts of machine learning and artificial intelligence, how these are applied to the field of morphological studies and what are the limits and potential of current technologies.

Prerequisites

None

Course unit content

Artificial intelligence is experiencing a period of great development, with applications in everyday life and in the sciences. The course illustrates the basic concepts of machine learning and how these can be applied to help in morphological disciplines

Full programme

Artificial intelligence and machine learning. Predictive models. Supervised and Unsupervised learning. Classification. Regression. Clustering. Neural networks. Deep Learning.

Bibliography

Materials for the course will be provided by the instructor.

Teaching methods

Lectures will be held on-site in compliance with safety standards, provided that further instructions on the ongoing health emergency are not implemented. Supporting material will be available on the specific, student-reserved platform (Elly) and will include slide presentations and video-recordings of the lectures.
Before each class, the instructor will first review the previous topics and assess whether they have been understood, through an interactive discussion with the students.

Assessment methods and criteria

- - -

Other information

- - -

2030 agenda goals for sustainable development

- - -

Contacts

Toll-free number

800 904 084

Student registry office

E.medicineandsurgery@unipr.it
 

Quality assurance office

Education manager:
Giovanna Caselli


Manager E  didattica.dimec@unipr.it

President of the degree course

Prof.Antonio Percesepe
E. antonio.percesepe@unipr.it

Faculty advisor TBD

Career guidance delegate TBD

Tutor Professor

[titolo] [nome] [cognome]
E. [email @unipr] 

Erasmus delegate

Prof.ssa Elena Masselli
E. elena.masselli@unipr.it
 

Quality assurance manager

Prof.Massimo Corradi 
E. massimo.corradi@unipr.it

Internships  TBD

Tutor students TBD