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.
Assessing the quality and educational applicability of AI-generated anterior segment images in ophthalmology.
AI-generated images in ophthalmology show promise for education, but expert validation is crucial. 📊👁️
From macroscopic clearance to molecular eradication: paradigm shift and future perspectives in the detecting of residual lesions after transurethral resection of bladder tumors.
Revolutionary advances in bladder cancer detection: molecular assessments enhance postoperative management and reduce recurrence...
Evolving HPV diagnostics: current practice and future frontiers.
Evolving HPV diagnostics: key advancements in detection methods and their impact on cervical cancer...
Brain benefits of deep learning-based noise management in experienced hearing aid users using functional near infrared spectroscopy.
Deep learning enhances hearing aids! 🎧 Study shows improved listening accuracy & reduced brain...
Artificial Intelligence for Predicting Lung Immune Responses to Viral Infections: From Mechanistic Insights to Clinical Applications.
AI predicts lung immune responses to viral infections, enhancing patient care and treatment strategies....
The global epidemiology, risk factors, and mortality prediction of nocardiosis: an easily missed opportunistic infection.
Nocardiosis: 9,750 cases analyzed; 19.8% mortality, 31.7% for disseminated infections. Machine learning predicts risks...
AI and Biotechnology to Combat Aflatoxins: Future Directions for Modern Technologies in Reducing Aflatoxin Risk.
AI and biotechnology offer innovative solutions to reduce aflatoxin risks in food safety. 🌾🤖
A novel approach to depression detection using POV glasses and machine learning for multimodal analysis.
Revolutionary POV Glasses & Machine Learning Detect Depression: 84.7% Accuracy, 90.9% Sensitivity! 🤖👓
Data augmentation alters feature importance in XGBoost for CVD prediction.
Data augmentation reshapes feature importance in CVD prediction models. Key findings: SMOTE model accuracy...