An AI-based algorithm for analyzing physical activity and health-related fitness in youth.
January 18, 2026AI-driven analysis boosts youth fitness assessments: 98.448% accuracy in classification and enhanced performance predictions. 📊🤖
Enhancing Developmental Language Disorder Identification with Artificial Intelligence: Development of an Explainable Screening App Using Real and Synthetic Data.
January 17, 2026AI-driven app enhances DLD identification, showing high concordance with clinical diagnoses. Key linguistic markers analyzed. 📊🤖
Leading large language models on a periodontology knowledge test.
January 17, 2026Large language models show 65% accuracy in periodontology tests, lacking reliability for clinical decision support. 📊🦷
Data Science Education for Residents, Researchers, and Students in Psychiatry and Psychology: Program Development and Evaluation Study.
January 17, 2026AI in Psychiatry Training: 10 trainees improved NLP confidence from 1.35 to 2.79! 📈💻 #DataScienceEducation
[Responsible use of AI and robotics in medicine : Opportunities, challenges and perspectives for otorhinolaryngology].
January 16, 2026AI and robotics in medicine: Transforming practices with ethical challenges. Key principles: transparency, shared responsibility, legitimacy. 🤖⚕️
Effects of Artificial Intelligence Recognition-Based Telerehabilitation on Exercise Capacity in Patients With Hypertension: Randomized Controlled Trial.
January 16, 2026AI telerehabilitation boosts exercise capacity in hypertension patients: 62.77m improvement in 6MWD after 8 weeks! 📈💪
Artificial intelligence-driven clustering for phenotyping life-threatening prehospital trauma.
January 16, 2026AI clusters trauma patients into three phenotypes, revealing 93.1% mortality in T-1 group. Key for emergency care! 🚑📊
Scoping review of regulatory transparency in AI-based radiology software: analysis of PMDA-approved SaMD products.
January 15, 2026Exploring AI in radiology: 2026 review on PMDA-approved software reveals transparency gaps. 📊🤖
AI-powered hierarchical classification of ampullary neoplasms: a deep learning approach using white-light and narrow-band imaging.
January 15, 2026AI-driven deep learning enhances ampullary lesion diagnosis: 92.2% accuracy, 83.3% sensitivity for high-grade dysplasia. 📊🔍