Discover the newest research about AI innovations in 🫁 Pulmonology.
A massive multi-center study reveals that the new 2026 AHA/ACC pulmonary embolism framework adds clinical complexity without improving risk prediction for the vast majority of patients.
A new deep learning model proves that combining visual breathing patterns with heart scans can predict which emergency patients will need a hospital bed.
Automating the search for mucus plugs in lung scans reveals a hidden driver of COPD mortality that human eyes routinely miss.
New AI Tool Improves Early Lung Cancer Detection 🫁💻. Late diagnosis remains a significant challenge, impacting survival rates.
AI in Chest Tube Management: CheLSEA’s 93% Accuracy in Removal Predictions 📊🤖
Revolutionary deep learning model predicts acute pulmonary embolism with 93.76% accuracy! 📊💡
Electrodermal activity shows promise in pain assessment, achieving 80% accuracy in detecting breakthrough pain. 📊💡
NICE recommends eight digital tools for asthma management, aiming to improve patient care and reduce health inequalities. 🌬️📱
New biosensor technology may enable lung cancer detection through breath analysis. Early diagnosis could improve patient outcomes. 🌬️🩺
Causal ML identifies patients with sepsis and AKI who benefit from restrictive fluid therapy. 🚑📊 Early AKI reversal rates improved significantly!
