BACKGROUND: Fatty liver disease is a common condition linked to metabolic syndrome, cardiovascular diseases, and liver cirrhosis, and timely, accurate diagnosis is crucial. In clinical studies, incorporating deep learning models often faces the chall...
Text emotion detection is an essential task in Natural Language Processing (NLP), with applications in customer support automation, diagnosing mental health, and social media analysis. Yet, precise emotion detection is a difficult problem as human em...
BACKGROUND: Preeclampsia is a severe hypertensive disorder with rising global prevalence. While machine learning (ML) models for predicting preeclampsia are increasingly published, existing evidence shows high heterogeneity, and the distinction betwe...
BACKGROUND: Effective communication is fundamental to health care; however, demographic transitions and a widening global health workforce gap are intensifying the imbalance between service demand and resource supply. Health conversational artificial...
BACKGROUND: The popularity of large language models (LLMs) has grown exponentially across health care. Despite the wealth of literature on proposed applications in medical education, there remains a critical gap regarding their real-world use, benefi...
Journal of molecular neuroscience : MN
Jan 19, 2026
Huntington's disease (HD) is a rare, inherited neurodegenerative disorder caused by the expanded CAG repeats in the huntingtin gene. The HD domain still lacks detailed knowledge of validated drug targets, limiting the effectiveness of classical metho...
The transition from laparoscopic to robotic surgery for left-sided colorectal cancer raises safety concerns during the learning curve, particularly when complex cases are preferentially selected for the robotic platform. We evaluated a machine learni...
European journal of clinical pharmacology
Jan 19, 2026
PURPOSE: The primary purpose of this study is to systematically evaluate how accurately artificial intelligence (AI) models can predict optimal warfarin dosing by incorporating both genetic variations-particularly in VKORC1 and CYP2C9-and clinical pa...
OBJECTIVE: This study aims to both develop and evaluate a predictive model for ureteral access sheath(UAS)placement success using preoperative CT-based 3D ureteral imaging and machine learning techniques. Specifically, it investigates the impact of u...
Predicting an individual's behavior in one task condition based on their behavior in a different condition is a key challenge in modeling individual decision-making tendencies. We propose a novel framework that addresses this challenge by leveraging ...
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