Automatic selection model to identify neurodegenerative diseases.

Objective: This study evaluates machine learning algorithms' effectiveness in classifying Parkinson's disease and Huntington's disease based on biomarker data obtained non-invasively from patients and healthy controls.

Methods: Datasets containing biomarker data (, , and values of accelerometers) from sensors were collected from Parkinson's disease, Huntington's disease patients, and healthy controls. An automatic selection model method was implemented for disease classification, using a unique Mexican database of human gait biomarkers, which we consider the only one of its kind.

The potential and challenges of Health 4.0 to face COVID-19 pandemic: a rapid review.

The COVID-19 pandemic has generated the need to evolve health services to reduce the risk of contagion and promote a collaborative environment even remotely. Advances in Industry 4.0, including the internet of things, mobile networks, cloud computing, and artificial intelligence make Health 4.