At the end of the course, the student masters the basic algorithms, tools and systems for the management, processing and analysis of dataset. The student is able to design and develop simple systems oriented to medical and biomolecular real-world problems. Principles of generative AI will also be part of the learning objectives, as well as their biomedical applications.

00. Course Introduction

01. Deep Learning
    01.01 Deep Learning Introduction
    01.02 Convolutional Neural Network
    01.03 Recurrent Neural Network
    01.04 Autoencoder, Transformers and Generative Adversarial Network

02. AI techniques applied to medical and biomolecular data analysis
    02.01 Types of Biomedical data
    02.02 Recap of data analysis methodologies
    02.03 The PyTorch library
    02.04 CNN Applications for medical imaging
    02.05 RNN Applications for medical signalling processing 

Although there are no mandatory prerequisites, it is advisable to follow this course after completing the courses of Machine Learning and Fundamentals of Artificial Intelligence.

The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it

Teaching

Theory lectures and laboratory exercises.

Attendance

Although recommended, course attendance is not mandatory.

Assessment

The exam consists of an oral discussion, where the student presents his/her project with explicit reference to the project goals, the consequent architecture, the implementation choices, providing adequate motivations. A presentation of a written report about the project together with a set of slides for a short presentation of the project is due. 

Disabilità e DSA

Le studentesse e gli studenti che hanno registrato la certificazione di disabilità o la certificazione di DSA presso l'Ufficio Inclusione e diritto allo studio, possono chiedere di utilizzare le mappe concettuali (per parole chiave) durante la prova di esame.

A tal fine, è necessario inviare le mappe, due settimane prima dell’appello di esame, alla o al docente del corso, che ne verificherà la coerenza con le indicazioni delle linee guida di ateneo e potrà chiederne la modifica.

Teaching

Same as attending.

Attendance

Same as attending.

Course books

Same as attending.

Assessment

The exam consists of an oral discussion, where the student presents his/her project with explicit reference to the project goals, the consequent architecture, the implementation choices, providing adequate motivations. A presentation of a written report about the project together with a set of slides for a short presentation of the project is due. 

Disabilità e DSA

Le studentesse e gli studenti che hanno registrato la certificazione di disabilità o la certificazione di DSA presso l'Ufficio Inclusione e diritto allo studio, possono chiedere di utilizzare le mappe concettuali (per parole chiave) durante la prova di esame.

A tal fine, è necessario inviare le mappe, due settimane prima dell’appello di esame, alla o al docente del corso, che ne verificherà la coerenza con le indicazioni delle linee guida di ateneo e potrà chiederne la modifica.