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A focused stream of research, industry developments and ideas selected for people building the future of health.
Research and developments, with a clear point of view.
![[Cough frequency monitoring: current technologies and clinical research applications].](https://yesilscience.com/wp-content/uploads/2025/09/Cough-frequency-monitoring-current-technologies-and-clinical-research-applications.jpg)
[Cough frequency monitoring: current technologies and clinical research applications].
Cough frequency monitoring: key technologies and clinical applications revealed in recent research. 📊🤒
AI Models Enhance Predictions for Chronic Kidney Disease Progression
AI models improve predictions for chronic kidney disease progression, aiding early detection and management....
Deep learning model using cross-sequence learning to identify orbital fractures in radiographs of patients under 20 Years.
Deep learning model detects orbital fractures in youth radiographs: AUROC 0.802, sensitivity 65.8%, specificity...
Improved Digital ECG Access at Barts Health Enhances Patient Care
Digital ECG access at Barts Health improves patient care, enabling faster decisions and reducing...
Social Media Recruitment in Indigenous and Native American Populations: Challenges in the AI Age.
Social media recruitment for Indigenous populations faces AI challenges. Limited success, data quality issues,...
Importance of Mentorship in Digital Health Leadership
Mentorship in digital health is vital for career growth and collaboration. It fosters confidence...
Predicting severe renal dysfunction in alcohol-associated cirrhosis: Comparative performance of liver function scores and machine learning models.
Predicting severe renal dysfunction in cirrhosis: MELD score shows 80% prevalence at high levels....
Remote MRI Scanning Pilot Reduces Patient Wait Times and DNA Rates
Remote MRI scanning pilot reduces patient wait times and DNA rates, enhancing flexibility and...
Comparative Evaluation of Clinical Large Language Models and Machine Learning to Predict Antimicrobial Resistance in Hospital-Onset Sepsis.
AI vs. Traditional ML in Predicting Antimicrobial Resistance: LLMs show 90%+ negative predictive value!...