Artificial Intelligence Medical Compendium

OBJECTIVE: Large language models are widely used in clinical care. Their reliability in specialized gynecological diseases such as premature ovarian insufficiency (POI) has not been fully verified. This study aimed to systematically evaluate and comp... 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 

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INTRODUCTION: Liver transplantation (LT) is a uniquely curative treatment for hepatocellular carcinoma (HCC), as it removes both the tumor and the underlying cirrhotic liver. However, organ scarcity makes candidate selection a central clinical and et... read more 

BACKGROUND: Breast MRI routinely uses gadolinium-based contrast agents (GBCAs) for dynamic contrast-enhanced (DCE) imaging. However, GBCA administration entails periprocedural effort and environmental impact, prompting exploration of contrast-agent-f... read more 

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 

Freshwater inflow regulates estuarine circulation, salinity gradients, sediment transport, and biogeochemical fluxes, yet long-term discharge records remain scarce in many tropical coastal basins. We compared linear regression, stochastic time-series... read more 

We developed THINKERS-X: Lung, the eXtended multimodal evolution of THINKERS-Lung, to determine whether multisequence MRI radiomics provides incremental value for lesion-specific outcome prediction and exploratory dose-scenario evaluation after Gamma... 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 

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