Dopaminergic therapy disrupts decision-making in impulsive-compulsive Parkinsonian patients.

Impulsive-compulsive behaviors (ICB) are common non-motor symptoms of Parkinson's disease (PD) often associated with dopaminergic drugs (DD) therapy. We investigated the acute effects of DD on decision-making in PD patients with ICB (ICB+) and without it (ICB-), and in healthy controls (HC). Participants performed a risk-based decision-making task twice, with PD patients tested before (DD OFF) and after (DD ON) DD intake.

An innovative artificial intelligence-based method to compress complex models into explainable, model-agnostic and reduced decision support systems with application to healthcare (NEAR).

Background And Objective: In everyday clinical practice, medical decision is currently based on clinical guidelines which are often static and rigid, and do not account for population variability, while individualized, patient-oriented decision and/or treatment are the paradigm change necessary to enter into the era of precision medicine. Most of the limitations of a guideline-based system could be overcome through the adoption of Clinical Decision Support Systems (CDSSs) based on Artificial Intelligence (AI) algorithms. However, the black-box nature of AI algorithms has hampered a large adoption of AI-based CDSSs in clinical practice.

Personalized modeling of Alzheimer's disease progression estimates neurodegeneration severity from EEG recordings.

Introduction: Early identification of Alzheimer's disease (AD) is necessary for a timely onset of therapeutic care. However, cortical structural alterations associated with AD are difficult to discern.

Methods: We developed a cortical model of AD-related neurodegeneration accounting for slowing of local dynamics and global connectivity degradation.