Discover the newest research about AI innovations in π¦ Epidemiology.
Machine learning models show 0.84 C-index for ARDS mortality prediction, outperforming traditional scoring systems. ππ‘
New platform BEACON enhances global infectious disease surveillance using AI and expert networks. ππ¦ Rapid threat detection and analysis.
Epidemiology of atopic dermatitis reveals 10-20% prevalence globally, with significant comorbidities like asthma and allergic rhinitis. ππ©Ί
Tinnitus risk factors identified: hearing health, mood, neuroticism, and sleep. Predictive model shows 78% accuracy! ππ
Predicting 28-day mortality in ICU immunocompromised patients using machine learning: SVM achieves AUROC of 0.863 ππ‘
AI predicts antibiotic resistance in bacteria, highlighting gene transfer in humans and wastewater. This research aids public health efforts. π¦ π¬
Machine learning π€ and conventional statistics π enhance health outcome predictions together, as shown in recent research.
A recent study developed an LSTM model to predict allergic rhinitis outpatient visits, enhancing treatment and prevention strategies. πΏπ
New research highlights personalized esophageal cancer risk prediction using genetic data and virtual alcohol consumption analysis. π·π
UKHSA explores AI to analyze restaurant reviews for food poisoning sources. This could enhance disease surveillance and outbreak prevention. π½οΈπ€
