Improvement of stereopsis following strabismus surgery in adults: a retrospective analysis.

Objective: Adults who undergo strabismus surgery, in addition to cosmesis, could benefit from improved stereopsis. This improvement is associated with the performance of motor skill tasks in young adults; they reduce the risk of tripping or falling during everyday locomotion and improve reading efficiency. This study aimed to assess stereopsis level after strabismus surgery in adults who underwent strabismus surgery for any reason.

Histopathologic and Molecular Insights Following the Management of Ameloblastomas via Targeted Therapies - Pathological and Clinical Perspectives.

Purpose: Current standard of care for ameloblastoma (conventional/unicystic - mural type) usually mandates extensive bone resection that frequently necessitates immediate reconstruction with serious sequelae, especially among young patients. BRAF-mutated ameloblastomas can be targeted by BRAF inhibitors to markedly reduce their size, enabling conservative removal of residual tumor. We aimed to characterize the effect of post-treatment histomorphologic changes.

Artificial intelligence improves risk prediction in cardiovascular disease.

Cardiovascular disease (CVD) represents a major public health issue, claiming numerous lives. This study aimed to demonstrate the advantages of employing artificial intelligence (AI) models to improve the prediction of CVD risk using a large cohort of relatively healthy adults aged 70 years or more. In this study, deep learning (DL) models provide enhanced predictions (DeepSurv: C-index = 0.

Navigating artificial intelligence in care homes: Competing stakeholder views of trust and logics of care.

The COVID-19 pandemic shed light on systemic issues plaguing care (nursing) homes, from staff shortages to substandard healthcare. Artificial Intelligence (AI) technologies, including robots and chatbots, have been proposed as solutions to such issues. Yet, socio-ethical concerns about the implications of AI for health and care practices have also been growing among researchers and practitioners.

A Systematic Review of Artificial Intelligence Models for Time-to-Event Outcome Applied in Cardiovascular Disease Risk Prediction.

Artificial intelligence (AI) based predictive models for early detection of cardiovascular disease (CVD) risk are increasingly being utilised. However, AI based risk prediction models that account for right-censored data have been overlooked. This systematic review (PROSPERO protocol CRD42023492655) includes 33 studies that utilised machine learning (ML) and deep learning (DL) models for survival outcome in CVD prediction.