Artificial Intelligence Medical Compendium

BACKGROUND: Empirical evidence demonstrating the influence of sex and gender on health has increased dramatically over the last two decades. Yet, the integration of this knowledge into medical school curricula remains limited. To address this gap, we... read more 

OBJECTIVES: Alveolar bone defects, such as fenestration and dehiscence, induced by orthodontic treatment represent significant complications that can impact treatment outcomes and long-term health. This study aims to develop a machine learning-based ... read more 

OBJECTIVE: The objective of this study is to evaluate the combined prognostic values of 18 F-fluorodeoxyglucose ( 18 F-FDG) PET and computed tomography (CT)-derived entropy-based heterogeneity features from hybrid PET/CT scanner using machine learnin... read more 

OBJECTIVE: Eye-tracking technology has been increasingly investigated as an objective approach for distinguishing individuals with Autism Spectrum Disorder (ASD) from typically developing (TD) individuals. Artificial intelligence and machine learning... read more 

BACKGROUND: The rise of digital health data has expanded opportunities for data-driven innovation, yet privacy, legal and ethical barriers frame data sharing and collaborative artificial intelligence development. Federated Learning (FL) offers a priv... read more 

BACKGROUND: Research on echocardiographic prognostication in non-obstructive coronary artery disease (CAD) is limited, mainly accompanied by different outcomes from obstructive CAD. This study developed machine learning (ML) models to predict clinica... read more 

In recent years, social media data has been widely applied in disaster management due to its large data volume, diverse content, low acquisition cost, and immediacy. However, the primary challenge in leveraging social media data for flood disaster ma... read more 

OBJECTIVE: A substantial proportion of patients (12 %-25 %) with recent small subcortical infarction (RSSI) suffer poor functional outcomes at 3 months. Despite the identification of prognostic factors, a significant gap exists in predictive modeling... read more 

OBJECTIVES: This study aimed to integrate soft tissue calcifications and ossifications (STCO) detected on cone beam computed tomography (CBCT) into an artificial intelligence (AI) system and assess its diagnostic accuracy in both single-class and mul... read more 

Physics-Informed Neural Networks (PINNs) have opened new possibilities for solving partial differential equations (PDEs) by embedding physical laws directly into the learning process. However, despite their flexibility, traditional PINNs often strugg... read more