Artificial Intelligence Medical Compendium

OBJECTIVES: Pelvic bones exhibit multiple secondary ossification centers during maturation, enabling automated age estimation. This study investigated whether a deep learning model could estimate chronological age from pelvic radiographs across the f... read more 

INTRODUCTION: The management of the long head of the biceps (LHB) tendon in small rotator cuff tears remains controversial, particularly when the tendon appears macroscopically healthy. While prophylactic tenotomy or tenodesis is often recommended fo... read more 

PURPOSE: Ambient artificial intelligence (AI) scribes, widely implemented to reduce clinician burden and dissatisfaction, are not optimized for oncology. We evaluated this technology at-scale at a high-volume cancer center. METHODS: This prospective ... read more 

OBJECTIVE: Soft tissue prediction is of great importance for the surgical design and patients ' satisfaction in orthognathic surgery. Previous studies either rely on elastic mechanical models, such as finite element which involves time-consuming comp... read more 

This study presents a multi-scale computational framework to quantify how externally applied acoustic waves propagate through the knee joint and induce mechanotransductive strain at the level of the chondrocyte nucleus. Patient-specific knee geometri... read more 

Antibiotic pollution in aquatic environments drives the spread of resistance genes and threatens ecosystem health. Microalgae offer a dual-function platform that both senses antibiotic stress and actively removes these contaminants. This review synth... read more 

Predicting functional outcomes in acute ischemic stroke (AIS) patients after endovascular thrombectomy (EVT) remains challenging due to the complex and dynamic nature of disease progression. Existing methods typically rely on single-stage imaging or ... read more 

Predicting functional outcomes in acute ischemic stroke (AIS) patients after endovascular thrombectomy (EVT) remains challenging due to the complex and dynamic nature of disease progression. Existing methods typically rely on single-stage imaging or ... read more 

In various studies, depressive symptoms, deviant peer association, and academic achievement appear to be reciprocally and cumulatively related across the transition from childhood to adolescence. This study asks a hypothetical question: how much woul... read more 

PURPOSE: The goal of this study was to enhance the fairness and clinical applicability of deep learning models for classifying Alzheimer's disease from structural MRI scans. To achieve this, we addressed two key challenges: age-related bias and unrel... read more