💤 Sleep

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Discover the newest research about AI innovations in 💤 Sleep.

Wrist trackers predict Parkinson’s disease years early

A new analysis of wearable data shows that tracking how we move during sleep can flag Parkinson’s risk a decade before clinical symptoms appear.

July 7, 2026

AI tracks sleep disorder severity using video

A new study shows video foundation models can grade violent sleep movements, but their tendency to overestimate severity reveals the limits of clinical AI.

July 6, 2026

Assessment of frontier Large Language Models in sleep medicine.

Evaluating ChatGPT-5 & Grok-4 in sleep medicine: 92.4% diagnostic accuracy, but limited differential diagnosis performance. 💤📊

May 15, 2026

Internally Validated Logistic Regression Nomogram for Depressive Symptoms Risk Prediction in Middle-Aged and Older Adults With Sarcopenia: Cross-Sectional Study.

Logistic regression model predicts depressive symptoms in sarcopenic adults. AUC 0.794, Brier score 0.065. Key factors identified. 📊🧠

April 7, 2026

Machine learning approached a 14-item shortened version of the Positive And Negative Sleep Appraisal Measure (PANSAM-14).

Machine learning refines sleep appraisal: PANSAM-14 shows R² scores up to 0.95 for predictive accuracy. 💤📊

March 25, 2026

Non-Contact Analysis of Cardiopulmonary Coupling via Video Technology

Non-contact video technology analyzes cardiopulmonary coupling, linking heartbeats and breathing for insights on health and sleep quality. 🫀💤

March 17, 2026

Leveraging explainable machine learning models to predict moderate to severe obstructive sleep apnea in heart failure with preserved ejection fraction patients: A comorbidity perspective.

Predicting OSA in HFpEF patients: RF model shows 0.974 AUC accuracy! 🤖💤 Key insights from PubMed study.

January 29, 2026

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