BACKGROUND: Gallbladder polyps have a high prevalence and are predominantly benign lesions, often detected via ultrasound. They impose diagnostic burdens on radiologists while generating substantial patient demand for report interpretation. Benign po...
Hematoma expansion is a consistent predictor of poor neurological outcome and mortality after spontaneous intracerebral hemorrhage (ICH). An incomplete understanding of its biophysiology has limited early preventative intervention. Transport-based mo...
BACKGROUND: The P53-mutated Hepatocellular Carcinoma (HCC) is an aggressive variant associated with vascular endothelial growth factor (VEGF) overexpression and increased microvascular density. This study aimed to develop an MRI-based deep learning m...
BACKGROUND: The development of immunotherapy has provided new hope for patients with advanced gastric cancer (AGC). However, due to the high heterogeneity of the disease, the efficacy of first-line immunochemotherapy varies among patients. There is s...
BACKGROUND: Health recommender systems (HRSs) are digital platforms designed to deliver personalized health information, resources, and interventions tailored to users' specific needs. However, existing evaluations of HRSs largely focus on algorithmi...
BACKGROUND: Accurate preoperative prediction of pathological complete response (pCR) following neoadjuvant chemoimmunotherapy (nCIT) could help individualize treatment for patients with esophageal squamous cell carcinoma (ESCC). This study aimed to d...
Journal of cancer research and clinical oncology
Dec 20, 2025
PURPOSE: With increasing reliance on large language models (LLMs) for health information, this study evaluated reliability and quality, understandability, actionability, readability and misinformation risk of responses from LLMs to oral health concer...
In this work, we propose three machine learning-based methods for predicting visual acuity (VA). Two methods utilize regression trees (LSBoost and XGBoost), and the third employs a neural network that classifies simulated aberrated optotypes as "reco...
BACKGROUND: Trust in artificial intelligence (AI) remains a critical barrier to the adoption of AI in mental health care. This study explores the formation of trust in an AI mental health model and its human-computer interface among clinicians at a w...
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