Artificial Intelligence Medical Compendium

BACKGROUND: Despite antiretroviral therapy (ART), 10-40 % of people living with HIV (PLWH) fail to normalize CD4+ T cells, known as immune non-responders (INR), associated with poor clinical outcomes. Due to the complex pathogenesis and the absence o... read more 

Existing data-driven models still exhibit shortcomings during short-duration precipitation events, with forecasts lacking multi-scale characteristics and overall intensity predictions tending to be low. Concurrently, improving forecasting accuracy of... read more 

Monitoring total suspended solids (TSS) in lakes at a global scale is critical for understanding lake ecosystem responses to climate change and anthropogenic activities. However, reliable retrieval methods for TSS global mapping remain elusive due to... read more 

Chemical-induced urinary tract toxicity, particularly in the bladder and ureters, remains undercharacterized relative to nephrotoxicity. We present an explainable QSAR framework that predicts urinary tract toxicity of defined chemicals using mechanis... read more 

PURPOSE: To determine whether retinal neovascularization (RNV) metrics derived from single-shot widefield swept-source OCT angiography (SS-OCTA) predict subsequent vision-threatening complications in eyes with high-risk proliferative diabetic retinop... read more 

OBJECTIVE: This study aimed to explore the feasibility of a discriminative correlation filter network (DCFNet)-based algorithm for positioning inconspicuous focal liver lesions (FLLs) on conventional US by tracking surrounding anatomical landmarks (S... read more 

Abdominal computed tomography (CT) is normally performed with patients raising their arms over abdominal region to prevent arm-induced artifacts that degrade image quality. This study aimed to evaluate the effects of deep learning-based image reconst... read more 

Artificial intelligence (AI) offers solutions to overcome limitations of fetal MRI, including motion, low signal-to-noise ratio, and slice misregistration. This review summarizes current AI applications in fetal MRI, focusing on image enhancement, au... read more 

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Automated seizure detection systems face significant challenges due to the limited availability of clinical EEG data, a substantial class imbalance between seizure and non-seizure recordings, considerable variability among patients, and the issue of ... read more