Predictive coding in neuropsychiatric disorders: A systematic transdiagnostic review.

The predictive coding framework postulates that the human brain continuously generates predictions about the environment, maximizing successes and minimizing failures based on prior experiences and beliefs. This PRISMA-compliant systematic review aims to comprehensively and transdiagnostically examine the differences in predictive coding between individuals with neuropsychiatric disorders and healthy controls. We included 72 articles including case-control studies investigating predictive coding as the primary outcome and reporting behavioral, neuroimaging, or electrophysiological findings.

The current clinical approach to feeding and eating disorders aimed to increase personalization of management.

Feeding and eating disorders (FEDs) are a heterogeneous grouping of disorders at the mind-body interface, with typical onset from childhood into emerging adulthood. They occur along a spectrum of disordered eating and compensatory weight management behaviors, and from low to high body weight. Psychiatric comorbidities are the norm.

Analysis of the haemodynamic changes caused by surgical and transcatheter aortic valve replacements by means fluid-structure interaction simulations.

Aortic valve replacements, both surgical and transcatheter, are nowadays widely employed treatments. Although clinically effective, these procedures are correlated with potentially severe clinical complications which can be associated with the non-physiological haemodynamics that they establish. In this work, the fluid dynamics changes produced by surgical and transcatheter aortic valve replacements are analysed and compared with an ideal healthy native valve configuration, employing advanced fluid-structure interaction (FSI) simulations.

The NACA score predicts mortality in polytrauma patients before hospital admission: a registry-based study.

Background: The early assessment of the severity of polytrauma patients is key for their optimal management. The aim of this study was to investigate the discriminative performance of the NACA score in a large dataset by stratifying the severity of polytraumatized patients in correlation to injury severity score (ISS), Glasgow Coma Scale (GCS), and mortality.

Methods: This study on the Swiss Trauma Registry investigated 2239 polytraumatized patient (54.

An advanced Artificial Intelligence platform for a personalised treatment of Eating Disorders.

Introduction: Eating Disorders (EDs) affect individuals globally and are associated with significant physical and mental health challenges. However, access to adequate treatment is often hindered by societal stigma, limited awareness, and resource constraints.

Methods: The project aims to utilize the power of Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), to improve EDs diagnosis and treatment.