Artificial Intelligence Medical Compendium

PURPOSE: To compare the utility of two large language models (LLM) in dry eye disease (DED) clinics and research. METHODS: Trained ocular surface experts generated 12 prompts for queries commonly asked by DED patients (n = 10 questions) and research ... read more 

Venous thromboembolism (VTE) remains a leading cause of cardiovascular morbidity and mortality, despite advances in imaging and anticoagulation. VTE arises from diverse and overlapping risk factors, such as inherited thrombophilia, immobility, malign... read more 

Anti-inflammatory peptides (AIPs) have emerged as potential therapeutic candidates for managing various inflammatory disorders, but their computational identification remains challenging. We propose AIP-TranLAC, a novel deep learning framework that i... read more 

BACKGROUND: Machine learning (ML) and artificial intelligence (AI) have demonstrated powerful functionality in the healthcare setting thus far. We aimed to construct an AI model to predict postoperative incontinence after enucleation surgery for beni... read more 

Deep learning has the potential to be a powerful tool for automating allele calling in forensic DNA analysis. Studies to date have relied on bespoke model architecture and painstaking manual annotations to train models, which makes it challenging for... read more 

Renal chronicity indices (CI) have been identified as strong predictors of long-term outcomes in lupus nephritis (LN) patients. However, assessment by pathologists is hindered by challenges such as substantial time requirements, high interobserver va... read more 

BACKGROUND: Immunotherapy represents a paradigm shift in oncology, offering advantages in efficacy and specificity over traditional therapies. Key to its success is the identification of T-cell antigens, which are essential for triggering an effectiv... read more 

BACKGROUND: The accurate identification of acupoints is an essential task in acupuncture therapy. Recent advancements in artificial intelligence (AI) have led to the exploration of automated landmark detection systems, which may provide more accurate... read more 

Maternal mortality remains a critical global public health issue, particularly in low- and middle-income settings where failures in surveillance, early diagnosis, and clinical decision making compromise obstetric care. In this context, the present st... read more 

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