AI Technology Estimates Biological Age from Facial Images to Enhance Cancer Prognosis
AI technology estimates biological age from facial images, aiding cancer prognosis and treatment decisions. 📸🧬
Evaluating User Interactions and Adoption Patterns of Generative AI in Health Care Occupations Using Claude: Cross-Sectional Study.
Generative AI in healthcare: 2.58% task usage, highest in patient-facing roles. Digital adoption rates vary (13.33%-65%). 📊🤖
Philips Report Reveals Trust Issues in Healthcare AI Between Clinicians and Patients
Philips report highlights trust issues in healthcare AI. Clinicians optimistic, but patients remain skeptical. 🤖💔
Exploring the potential of anticancer peptides as therapeutic agents for cancer treatment.
Anticancer peptides show promise in targeting tumors with low toxicity. Key findings from PubMed article reviewed. 🧬💊
Coreline Soft Secures AI Imaging Contracts with NHS and Boehringer Ingelheim
Coreline Soft secures AI imaging contracts with NHS and Boehringer Ingelheim, enhancing medical image analysis in healthcare. 🏥📊
25 Years of Digital Health Toward Universal Health Coverage in Low- and Middle-Income Countries: Rapid Systematic Review.
Digital health in low-income countries evolved from SMS to apps, enhancing care access. COVID-19 accelerated this transformation. 📱🌍
Cyber Incident at Two NHS Trusts Raises Concerns Over Data Security
Cyber Incident at NHS Trusts Raises Data Security Concerns 🏥🔒. NHS England investigates potential vulnerabilities in software used for mobile device management.
Enhancing search strategies for systematic reviews on drug Harms: An evaluation of the utility of ChatGPT in error detection and keyword generation.
ChatGPT enhances drug harm reviews: 49% keyword recreation, 0.17 Jaccard similarity. Effective error detection tool! 📊💊
Enhancing Healthcare with AI-Native Networking Solutions
AI-native networking enhances healthcare by improving data flow, supporting AI applications, and addressing cybersecurity threats. 🏥💻
Behavior recognition technology based on deep learning used in pediatric behavioral audiometry.
Deep learning enhances pediatric audiometry accuracy: sensitivity up to 0.943, specificity 0.947. Real-time monitoring improves hearing assessments. 📊👶