Ander Barrio 2022

Amaitua

Ikerketa lerroa:

Fairness & gender analysis

Azalpena:

Non-motor manifestations of Parkinson¿s disease (PD) appear early and have a significant impact on the quality of life of patients, but few studies have evaluated their predictive potential with machine learning algorithms. On the other hand, males and females have different patterns of illness and different life spans. Understanding the bases of these sex-based differences is important to developing new approaches to prevention, diagnosis, and treatment. In addition machine learning solutions suffer from biases derived from data used to train them. The aim of this project is to analyse the influence of sex in diagnostic classification of Parkinson's disease based on non-motor manifestations by means of machine learning methods in in two cohorts; one form Biocruces and another one from PPMI.

Partehartzaileak:

Zuzendaria(k):

Olatz Arbelaitz

Unibertsitatea:

Universidad del País Vasco/Euskal Herriko Unibertsitatea (UPV/EHU)

Zentroa:

Informatika Fakultatea - Facultad de Informática

Saila:

Konputagailuen Arkitektura eta Teknologia - Arquitectura y Tecnología de computadores

Irakurketaren data:

2022-07-04

Irakurketaren urtea:

2022