Checking date: 10/06/2022

Versión en español

Course: 2023/2024

AI in Health
(19216)
Master in Applied Artificial Intelligence (Plan: 475 - Estudio: 378)
EPI


Coordinating teacher: ARTES RODRIGUEZ, ANTONIO

Department assigned to the subject: Signal and Communications Theory Department

Type: Electives
ECTS Credits: 3.0 ECTS

Course: 1º
Semester: 2º



Requirements (Subjects that are assumed to be known)
None
Objectives
The objectives of the matter are: 1) to present the possibilities and limitations of the application of AI in the field of health, 2) to present problems in the field of health in which AI techniques can be applied, and 3) develop the capacity to apply AI techniques in some health problems.
Skills and learning outcomes
Link to document

Description of contents: programme
1. Introduction to AI in health 2. AI for diagnosis 3. Patient monitoring 4. Interpretability and validation 5. Risk stratification in patients 6. AI for hospital management
Learning activities and methodology
Theorical class Practical classes Practical theoretical classes Laboratory practices Tutoring Team work Individual student work Midterm and final exams
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100
Calendar of Continuous assessment
Basic Bibliography
  • James M. Rehg, Susan A. Murphy, Santosh Kumar. Mobile Health: Sensors, Analytic Methods, and Applications. Springer. 2017
  • Kevin Patrick Murphy. Probabilistic Machine Learning: An Introduction. MIT Press. 2022

The course syllabus may change due academic events or other reasons.