Convolutional Neural Networks in Chronic Wound Segmentation and Tissue Classification Using Real-World Images.
AI in Chronic Wound Care: CNNs Achieve DSC of 0.927 📊, IoU of 0.868 for Segmentation! 🩹
Study Reveals Limitations in AI Medical Triage Systems
Study shows AI medical triage systems may misdirect users in serious cases, raising concerns about emergency care access. ⚠️🩺
A machine learning model to simplify recognition of patients with atrial fibrillation based on diagnostic codes in Swedish primary health care.
Machine learning enhances atrial fibrillation detection in Swedish healthcare, improving diagnostic accuracy and patient outcomes. 📊❤️
Potential Review of Palantir’s NHS Contract Amidst Performance Concerns
Palantir's NHS contract may face review due to performance issues. Alternatives could be considered if they prove more effective. 🏥📊
Chest Tube Learning Synthesis and Evaluation Assistant (CheLSEA): A Prospective Observational Trial of an Intelligent Decision Support System.
AI in Chest Tube Management: CheLSEA's 93% Accuracy in Removal Predictions 📊🤖
Concerns Over AI Cancer Tools Relying on Statistical Shortcuts
AI cancer tools may depend on shortcuts, raising concerns about their reliability in diagnosing cancer accurately. 🧬🔍
Use of Deep Learning Models in the Diagnosis of Proptosis Through Orbital Magnetic Resonance Imaging.
Deep learning models show 95% accuracy in diagnosing proptosis via MRI, enhancing objectivity in orbital disease assessment. 🧠📊
Artificial intelligence in cancer survivorship: evaluating ChatGPT’s performance in rehabilitation-related queries.
AI in Cancer Rehab: ChatGPT's Accuracy at 3.93/5 📊, Completeness 2.13/3 📋, Global Quality 3.60/5 🌟.
Cheshire East’s Neighbourhood Care Model Decreases Emergency Room Visits
Cheshire East's neighbourhood care model reduces emergency room visits by up to 48%. A significant step in community health. 🏥📉
Explainable machine learning for predicting infections that require hospitalization in patients with systemic lupus erythematosus.
Predicting hospitalizations in SLE patients using AI: 88% AUROC, 15 key predictors identified. 🤖📊