Artificial Intelligence Medical Compendium

There is a gap in real-world clinical adoption of machine learning (ML) solutions due to the inherent uncertainty and variability in treatment outcomes. To bridge this gap, we present a novel approach to the problem of medical treatment selection usi... read more 

BACKGROUND: Delirium remains one of the most consequential complications among critically ill patients in ICUs, exerting profound effects on morbidity, mortality, and annual healthcare costs exceeding $81 billion. Communication barriers between sedat... read more 

INTRODUCTION: Until recently, the widespread use of genetic markers in prostate cancer (PCa) has been limited by the complexities and cost of genomic data analysis. Artificial intelligence (AI), due to its ability to process large volumes of unstruct... read more 

BACKGROUND: Clinical practice currently lacks objective and accurate screening tools for minimal hepatic encephalopathy (MHE). Therefore, we aimed to develop an MHE prediction model based on common risk factors. METHODS: A total of 514 and 191 cirrho... read more 

The rapid advancement of generative artificial intelligence (AI) has led an increasing number of Chinese patients to incorporate AI tools into their clinical encounters. While prior research has explored individual attitudes toward AI-mediated diagno... read more 

BACKGROUND CONTEXT: Manual measurement of cervical sagittal parameters is time-consuming and exhibits significant interobserver variability. Existing artificial intelligence models fail when C7 is obscured by shoulder anatomy. PURPOSE: To develop and... read more 

MOTIVATION: Identifying drug-target interactions (DTIs) is a critical step in both drug discovery and drug repurposing. Accurate in silico prediction of DTIs can substantially reduce development time and costs. Recent advances in sequence-based metho... read more 

Lameness is a major welfare and productivity concern in dairy herds. This study investigated the influence of animal traits (parity, BCS) and environmental factors (farm, season) on locomotion score (LS) in lactating cows and assessed the impact of l... read more 

INTRODUCTION: Moyamoya disease (MMD) and syndrome (MMS) are rare cerebrovascular arteriopathies marked by progressive internal carotid stenosis, fragile collateral networks, and a five-year stroke risk near 10% despite optimal care. Artificial-intell... read more 

OBJECTIVE: To construct and validate a model for predicting lymph node metastasis (LNMs) of gastric cancer (GC) based on 18F-FDG PET/CT multi-parameter data and multiple machine learning (ML) algorithms. METHODS: We conducted a retrospective analysis... read more