Evaluating EPR Usability Data and Its Impact on NHS
Evaluating EPR usability data may significantly influence NHS efficiency and patient care. Insights from Thomas Webb highlight potential improvements. 📊🏥
Explainable machine learning for long-term cardiovascular disease risk prediction in Chinese middle-aged and older adults: a 9-year longitudinal cohort study with web-based risk calculator.
Machine learning predicts cardiovascular risk in Chinese adults: 22% incidence, AUC 0.829, waist circumference key factor. 📊❤️
Antimicrobial discovery from underexplored environments: unlocking specialized metabolism.
Exploring new antibiotic sources: AI, multi-omics, and ecology combat AMR crisis. 🦠🔬📈
Mandatory Professional Registration for Digital Health Staff in NHS
NHS England mandates digital health staff to register with professional bodies. This aims to enhance standards in digital healthcare. 🏥💻
SGA-DT: An adaptive fusion framework for missing data imputation and interpretable healthcare classification.
SGA-DT framework enhances healthcare predictions by addressing missing data with adaptive strategies. 📊🤖 Robust, interpretable, and accurate!
FDP Benefits Limited by Central Clarity Issues
FDP benefits are hindered by unclear guidance from central authorities, impacting digital health advancements. 🏥🔍
Radiomics and artificial intelligence-based prediction of tumor response in digestive system neoplasm: a systematic review and meta-analysis.
Radiomics & AI enhance tumor response prediction in GI neoplasms. Key findings: ORs range from 8.12 to 11.62. 📊🔍
Comment on Topaloglu et al. Machine Learning-Driven Lung Sound Analysis: Novel Methodology for Asthma Diagnosis. Adv. Respir. Med. 2025, 93, 32.
Exploring machine learning in asthma diagnosis: Topaloglu et al.'s innovative lung sound analysis method. 📊🫁