ARTIFICIAL INTELLIGENCE APPLICATIONS IN MEDICINE
Academic year and teacher
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- Versione italiana
- Academic year
- 2021/2022
- Teacher
- EVELINA LAMMA
- Credits
- 5
- Didactic period
- Secondo Semestre
- SSD
- ING-INF/05
Training objectives
- Understand the potential offered by Artificial Intelligence tools for the treatment of knowledge and data in the medical field. As future doctor, be aware of the potential offered by artificial intelligence technologies when applied to medicine.
Prerequisites
- Attendance of a basic course on computer science applications and tools.
Course programme
- The course is organized in five modules, 1 CFU each. Contents are:
Module 1 - 1 CFU
Introduction to Artificial Intelligence
First Order Logic as representation language
Rule-based systems and Decision Support Systems (DSS)
Applications: case study DSS for clinical exams
Practical exercises for rule formalization
Module 2 - 1 CFU
Constraint problems
Constraint representation and search techniques in solution space
Applications in the medical-health field, examples
Module 3 - 1 CFU
Unsupervised learning
Clustering, association rules
Data mining systems
Medical data applications (with open source databases)
Exercises with the Weka framework
Module 4 - 1 CFU
Automatic Machine Learning systems
Supervised Learning systems
Classification
Neural Networks (fundaments), with Computer Vision applications
Applications in the medical-health field, examples
Practical exercises using the framework Weka
Module 5 - 1 CFU
What is an ontology: basic concepts
Ontologies in Medicine
Inference systems for ontologies
Practical exercises Didactic methods
- Teaching activity is carried out partly with lessons and practical exercises, and partly via the Moodle platform.
Learning assessment procedures
- The final exam tests the degree of achievement of the training objectives indicated above.
Students are partly evaluated through the evaluation by the teacher of the assigned exercises, and through a final exam about the topics presented during the lessons. Reference texts
- Slides, and papers provided by teachers of each module.
