Importance of Mentorship in Digital Health Leadership
Mentorship in digital health is vital for career growth and collaboration. It fosters confidence and innovation in challenging environments. 🌐🤝
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. Machine learning enhances accuracy! 📊🔍
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 training efficiency. 🏥📉
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! 📊💉
Patients Know Best Receives Investment to Enhance Patient Record System
Patients Know Best secures investment from DNV to enhance its personal health record system and expand internationally. 🌍📈
Machine Learning Approach for Frailty Detection in Long-Term Care Using Accelerometer-Measured Gait and Daily Physical Activity: Model Development and Validation Study.
Machine learning detects frailty in long-term care with 86.3% accuracy using accelerometer data. 📊👵 #HealthTech
Robotic-Assisted Surgery Initiative Reduces Patient Waiting Times
Robotic-assisted surgery at Sandwell and West Birmingham NHS Trust reduces patient waiting times. 🏥🤖 Eight patients treated efficiently.
Artificial Intelligence in Cardiovascular Health: Insights into Post-COVID Public Health Challenges.
AI transforms cardiovascular health post-COVID, enhancing risk prediction and real-time monitoring. Key for public health strategies! 🫀📊
Addressing the Challenges of Ambient Scribe Technology in Mental Health
Ambient Scribe Technology in mental health poses challenges. Patient trust and clinician workload must be balanced for effective care. 🧠💬
Risk prediction model for post-endoscopic retrograde cholangiopancreatography pancreatitis: A systematic review and meta-analysis.
"PEP risk models show 8.48% incidence; predictors include pancreatic duct cannulation (OR=3.50) and previous pancreatitis (OR=3.32). 📊🔍"