The aim is to present expert-agreed guidelines for the primary prevention of cardiovasculotoxicity of anticancer therapy as part of the Cardioprotection 2025 Consensus of the Russian Society of Cardiology, the Society of Heart Failure Specialists, th...
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: Traditional, complementary, and integrative (TCI) medicine is an essential component of health systems worldwide, especially in low- and middle-income countries. Despite its widespread use, existing research on the safety, efficacy, and i...
PURPOSE: Artificial intelligence (AI) has become incredibly popular over the past several years, with large language models (LLMs) offering the possibility of revolutionizing the way healthcare information is shared with patients. However, to prevent...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Nov 3, 2025
Metastatic castration-resistant prostate cancer has a high rate of mortality with a limited number of effective treatments after hormone therapy. Radiopharmaceutical therapy with [Lu]Lu-prostate-specific membrane antigen-617 (LuPSMA) is one treatment...
BACKGROUND: Information extraction (IE) from clinical texts is increasingly important in health care; yet, reporting practices remain inconsistent. Existing guidelines do not fully address the unique challenges of IE studies. IE methods vary widely i...
The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of chatbots driven by generative artificial intelligence when summarizing clinical evidence a...
Journal of chemical information and modeling
Sep 12, 2025
A carcinogenicity assessment of possibly carcinogenic chemicals (International Agency for Research on Cancer: IARC class 2B) was conducted using a consensus framework constructed from three complementary machine learning models: BiLSTM with MACCS fin...
BACKGROUND: Deep learning can automate nerve identification by learning from expert-labeled examples to detect and highlight nerves in ultrasound images. This study aims to evaluate the performance of deep-learning models in identifying nerves for ul...
INTRODUCTION: Cluster analysis, a machine learning-based and data-driven technique for identifying groups in data, has demonstrated its potential in a wide range of contexts. However, critical appraisal and reproducibility are often limited by insuff...
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