NHS National Rehabilitation Centre to Introduce Smart Bedside Terminals
NHS National Rehabilitation Centre to implement smart bedside terminals for patient independence and enhanced care. 🛏️📱
Teaching postsecondary students about the ethics of artificial intelligence: A scoping review protocol.
Exploring AI Ethics in Education: A Scoping Review on Teaching Strategies and Outcomes 📚🤖
AI Model Enhances Tumor Detection in Breast MRI
AI model improves tumor detection in breast MRI, enhancing accuracy and efficiency for better cancer screening. 🩺📊
TCN-MAML: A TCN-Based Model with Model-Agnostic Meta-Learning for Cross-Subject Human Activity Recognition.
Innovative TCN-MAML model achieves 99.6% accuracy in cross-subject human activity recognition using Wi-Fi sensing! 📊📡
Data Sharing and IT Challenges in Prison Healthcare Impact Patient Safety
Prison healthcare faces challenges due to poor data sharing and IT systems. This impacts patient safety and care quality. 🏥🔒
Weekly Health & AI Digest – July 28, 2025
Here are the latest breakthroughs in health & AI (July 28, 2025 week) 🔹 AI Enhances Clinical Trials for Alzheimer’s Drug Development AI improves Alzheimer’s drug trials by accurately identifying patient groups, potentially speeding up effective treatment development. 🧠💊 ——-...
AI Enhances Clinical Trials for Alzheimer’s Drug Development
AI improves Alzheimer's drug trials by accurately identifying patient groups, potentially speeding up effective treatment development. 🧠💊
To What Extent Can Digital Health Technologies Comply With the Principles of Responsible Innovation? Practice-and Policy-Oriented Research Insights Regarding an Organisational and Systemic Issue.
Digital health technologies' compliance with Responsible Innovation principles hinges on organizational culture, resources, and regulatory frameworks. 📊💡
NHS 10-Year Health Plan: Addressing Health Tech Procurement Challenges
NHS 10-Year Health Plan aims to tackle procurement challenges in healthcare technology. Collaboration is key for innovation. 🤝💡
Beyond labels: determining the true type of blood gas samples in ICU patients through supervised machine learning.
Machine learning enhances blood gas sample accuracy in ICU: 33,800 samples analyzed, achieving AUCPR of 0.9974! 📊💉