NHS Hospitals Implement AI Tool to Anticipate A&E Demand
NHS hospitals in England are using an AI tool to predict A&E demand, improving patient care and resource management. 🏥🤖
January 6, 2026
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Discover the newest research about AI innovations in 🩹 Emergency.
Health Tech Suppliers Share Insights for 2026
Health tech suppliers predict significant advancements in NHS technology by 2026, focusing on AI integration, patient-centered care, and improved data management. 🏥💻
January 2, 2026
Evaluating AI-based comprehensive clinical decision support for sepsis and ARDS: protocol for a Clinician Turing Test.
AI in sepsis care: Clinician Turing Test to assess decision support safety and effectiveness. 🤖🩺
December 29, 2025
Artificial Intelligence and Radiogenomics for Pediatric CNS Neoplasms.
AI & Radiogenomics in Pediatric CNS Tumors: 2021 WHO guidelines enhance diagnosis via molecular profiling. Promising future ahead! 🧠✨
November 23, 2025
Predicting hospice eligibility among dementia patients using language models.
GPT-4o predicts 6-month mortality in dementia patients, aiding hospice referrals with AUC of 0.79 and aHR of 31.02. 📊💡
November 13, 2025
Implementation, Experiences, Impact, and Costs of Artificial Intelligence in Chest Diagnostics: Protocol for a Mixed Methods Evaluation.
AI in Chest Diagnostics: Evaluating Implementation, Costs, and Experiences in NHS Networks 📊🤖
November 1, 2025
AI-Enhanced Wearable Device Accelerates Wound Healing
AI-Enhanced Wearable Device Speeds Up Wound Healing 🩹🤖. The “a-Heal” device uses AI and bioelectronics for personalized treatment.
October 14, 2025
Foreign body removal.
Airway foreign body aspiration poses risks, especially in children and seniors. Recent studies show 98-99% diagnostic accuracy with advanced imaging. 🩺🔍
October 13, 2025
Development and evaluation of a machine learning prediction model for short-term mortality in patients with diabetes or hyperglycemia at emergency department admission.
Machine learning predicts 30-day mortality in diabetes patients at ED with 86-97% sensitivity. 📊⚕️
October 5, 2025
Deep learning model using cross-sequence learning to identify orbital fractures in radiographs of patients under 20 Years.
Deep learning model detects orbital fractures in youth radiographs: AUROC 0.802, sensitivity 65.8%, specificity 86.5%. 📊👁️
September 18, 2025