SE3.1) Estructurar datos a partir de fuentes multimodales y no estructuradas para inferir nuevo conocimiento SE3.4) Desarrollar herramientas de asistencia al diagnóstico y toma de decisión en salud SE3.2) Evaluar algoritmos de análisis de imagen destinados a solucionar problemas específicos de salud
Tipus d’activitat Hores amb professor Hores sense professor Hores virtuals amb professor Total Anàlisi / estudi de casos 0 43,50 5,50 49,00 Sessió participativa 0 9,00 17,00 26,00 Total 0 52,50 22,50 75
Karri Haen Whitmer (2022). A Mixed Course-Based Research Approach to Human Physiology. Iowa State University Digital Press. Friston, K. J. (Karl J.) (2007). Statistical parametric mapping : the analysis of functional brain images (1st ed.). London: Academic Catàleg M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, S.M. Smith (2012). FSL. NeuroImage, 62(2), Mark Jenkinson, Michael Chappell (2021). Introduction to Neuroimaging Analysis. Oxford University Press. Bielza, Concha (2021). Data-driven computational neuroscience: machine learning and statistical models. Cambridge, UK ;: Cambridge University Press. Catàleg
Activitats d'avaluació: Descripció de l'activitat Avaluació de l'activitat % Recuperable Test activities 35 No Problem with practical component about EEG signal processing Evaluation criteria will be provided with the problem description. 35 No Problem with practical component about image analysis on neuroimages. Evaluation criteria will be provided with the problem description. 30 Sí
The final mark of the subject will be calculated according to the weights of each of the proposed activities. This module promotes the critical and responsible use of artificial intelligence tools as part of the learning process. In some activities, the use of AI may be required or permitted, always in accordance with the specific instructions from the teaching staff, which can be found in the virtual learning environment. There may also be activities where their use is explicitly prohibited. In case of doubt regarding their use, students are advised to consult the teaching staff beforehand. Any use of artificial intelligence tools must be duly declared by the student, in accordance with the declaration instructions provided by the teaching staff. Unauthorised use of artificial intelligence tools will be sanctioned in accordance with current regulations Fraudulent conduct in any assessment activity, by any means, will result in the student receiving a failing grade for that activity. Furthermore, depending on the severity of the misconduct, the school may propose the initiation of disciplinary proceedings, which shall be formally instituted by a decision of the rector. Criteris específics de la nota «No Presentat»: NP will be considered when the students do not submit any of the evaluation activities. Avaluació única: This is an interuniversity program, that does not consider this kind of evaluation. Requisits mínims per aprovar: The minimum qualification to pass the course is 5.0
To stablish the apointments, students can user or sent mails to the professors. These appointments can be done online via googlemeet / zoom / TAEMS metting.
The communication and interaction with the students will be mainly done via moodle, having also specific forums for the activities. Students can also interact with the professors via email or via videoconferences (googlemeet, zoom, TEAMS).
Updated information in the Moodle of the Master site https://guiadocent.urv.cat/guido/public/centres/527/ensenyaments/3745/assignatures/119016/guia_docent