1. Introduction. Overview of techniques, application fields in medical areas. Diagnosis and Healthcare models’ history. 2. Computer assisted diagnosis. • Computer assisted diagnosis under traditional Healthcare and Medicine. • Computer assisted diagnosis for 4P Medicine • Computer assisted diagnosis under new Healthcare, decentralized models. Monitoring at home. Digital twins 3. Decision support systems. • Intelligent decision making for supporting diagnosis: optimizing resources and services • Recommender systems: supporting clinical decision making for managing medical evidence in diagnosis • Empowering patients for better medicine outcomes • Machine learning to close the loop between medical evidence and diagnosis 4. Study cases • Monitoring systems: monitoring babies at home. Falling detection systems. EEG and mental health. • Managing diseases: multi-comorbidity patients, tobacco quitting patients, patients with high blood pressure • Medical evidence: Use of literature to best ADHD treatment • Resource management: prioritize patient attendance in ICUs • Others: Decision systems for initial diagnosis of rare diseases.
Tipus d’activitat Hores amb professor Hores sense professor Hores virtuals amb professor Total Aprenentatge basat en problemes (PBL) 0 30,00 15,00 45,00 Prova d'avaluació 0 4,00 3,00 7,00 Seminaris 0 2,00 4,00 6,00 Sessió expositiva 0 5,00 10,00 15,00 Sessió participativa 0 3,00 6,00 9,00 Sessió pràctica 0 20,00 10,00 30,00 Tutories de grup 0 0 0,50 0,50 Total 0 64,00 48,50 112,5
Russell, Stuart J. (Stuart Jonathan) (2021). Artificial intelligence : a modern approach (Fourth edition). Upper Saddle River: Pearson. Catàleg Chang, Mark (2020). Artificial intelligence for drug development, precision medicine, and healthcare. Boca Raton: CRC Press. Catàleg
Activitats d'avaluació: Descripció de l'activitat Avaluació de l'activitat % Recuperable Labs 30 No Problem-based learning 40 No Test 30 No
The final mark of the subject will be calculated according to the weights of each of the proposed activities Criteris específics de la nota «No Presentat»:NP will be considered when the students do not submit any of the evaluation activities Avaluació única:Students should do an exam related to the contents seen in the course (both theoretical an practical concepts). Requisits mínims per aprovar:The minimum qualification to pass the course will be 5.0
To stablish the apointments, students can use or sent mails to the prefessors. These appointments can be done online via googlemeet / zoom / TAEMS meeting or in person (professors offices).
The communication and interaction with the student will be mainly done via moodle, having also specific forums for the activities. Students can also interact with the teacher via email or via videoconferences (googlemeet, zoom, TEAMS).
This subject is conducted in collaboration with Prof. Rui Alves (from Universidad de Lleida). Additional articles from magazines and international conferences will be provided. Updated information in the Moodle of the Master site (https://www.urv.cat/en/studies/master/courses/biomedical-data-science/)