Signals shaping
health AI.
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.
Limited Launch of Scotland’s Digital Front Door App for Dermatology Patients
Scotland's Digital Front Door app for dermatology patients launches in Lanarkshire, focusing on limited...
Proposing core competencies for physicians in using artificial intelligence tools in clinical practice.
Core competencies for physicians using AI tools in healthcare are essential for improved patient...
NHS App to Enhance Mental Health Support with AI Features
NHS App introduces AI features for improved mental health support. Patients can self-refer for...
Machine learning algorithms in predicting survivability of patients with renal cell carcinoma after nephrectomy: a retrospective study.
Machine learning enhances RCC survivability predictions post-nephrectomy. LASSO-Cox model shows 5-year AUC of 0.880!...
European Respiratory Society Clinical Practice Guideline on Telemedicine in Home Mechanical Ventilation.
Telemedicine in Home Mechanical Ventilation: ERS Guidelines Highlight Conditional Recommendations for COPD & Neuromuscular...
New Electronic Patient Record System Approved for GP Practices in England
New electronic patient record system approved for GP practices in England. 🏥💻 Enhances patient...
![[The analysis of invention patents in the field of artificial intelligent medical devices].](https://yesilscience.com/wp-content/uploads/2025/06/The-analysis-of-invention-patents-in-the-field-of-artificial-intelligent-medical-devices.jpg)
[The analysis of invention patents in the field of artificial intelligent medical devices].
Exploring AI Medical Devices: Patent Trends, Key Players, and Innovations 📈🤖
New AI Tool on NHS App Aims to Reduce Health Inequalities
New AI tool on NHS App aims to improve access to health information and...
Forecasting Achievement of Inactive Disease in Juvenile Idiopathic Arthritis with Artificial Intelligence.
AI predicts inactive disease in juvenile idiopathic arthritis: 68 predictors, 414 patients, 0.68 MCC!...