Jon Ander Arnal 2024

Finished

Research line:

Health informatics

Description:

Parkinson’s disease (PD) is the second most common neurodegenerative condition after Alzheimer’s disease and affects up to 1% of the population above 60 years. In this context, early diagnosis and detection can improve the quality of life of the patients. Prodromal patients are patients showing symptoms that might transform within parkinsonism, and and thus, detecting who is eligible to develop the pathology will be of great help. The PPMI database contains longitudinal information of prodromal patients where a few patients who phenoconverted in a period of 7 years can be identified rising to an imbalanced database. The information contained in the database is of diverse nature such as demographic information, motor and non-motor information extracted from clinical tests, bio-specimens and different types of scans. The aim of this project is to build classifiers and methods to face the class imbalance problem and to analyse to what extent the identification of phenoconverted patients can be done using clinical data and tests (without using image information).

Participants:

Director(s):

Javier Muguerza
Olatz Arbelaitz

University:

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

Center:

Informatika Fakultatea - Facultad de Informática

Department:

Konputagailuen Arkitektura eta Teknologia - Arquitectura y Tecnología de computadores

Reading year:

2024