SSC-SleepNet: A Siamese-Based Automatic Sleep Staging Model with Improved N1 Sleep Detection.
Revolutionary SSC-SleepNet enhances N1 sleep detection in EEG, achieving F1-scores up to 60.2%! π€π
May 24, 2025
Follow us
latest articles
Discover the newest research about AI innovations in π€ Sleep.
Tinnitus risk factors and its evolution over time.
Tinnitus risk factors identified: hearing health, mood, neuroticism, and sleep. Predictive model shows 78% accuracy! ππ
May 8, 2025
Analog to Digital Diagnosis and Planning in Orthognathic Surgery: A Narrative Review.
Innovations in orthognathic surgery enhance precision and outcomes. Key advancements include AI, 3D imaging, and virtual planning. π¦·β¨
April 22, 2025
Toward an Automatic Classification of the Different Stages of Sleep: Exploring Patterns of Neural Activity in the Subthalamic Nucleus.
Exploring subthalamic nucleus activity reveals 94% accuracy in classifying sleep stages, aiding sleep disorder therapies. π§ π€
April 15, 2025
The future of paediatric sleep medicine: a blueprint for advancing the field.
Paediatric sleep medicine is evolving. π Key topics include climate impact, education, and technology’s role in improving children’s sleep. π€
March 29, 2025
Artificial intelligence in obstructive sleep apnea: A bibliometric analysis.
AI is transforming obstructive sleep apnea research. π Key trends include deep learning and personalized treatment. π€
March 24, 2025
AI Algorithm Developed by Mount Sinai to Diagnose Sleep Disorder
Mount Sinai has developed an AI algorithm to diagnose REM sleep behavior disorder (RBD) with high accuracy. π€π€
March 17, 2025
Development of a Voice-Activated Virtual Assistant to Improve Insomnia Among Young Adult Cancer Survivors: Mixed Methods Feasibility and Acceptability Study.
A recent study explored a voice-activated assistant to help young adult cancer survivors manage insomnia. π€π±
March 11, 2025
Women Entrepreneurs Shine at UK Women in Innovation Awards
Women entrepreneurs excelled at the UK Women in Innovation Awards, showcasing innovative health tech solutions. ππ‘
February 10, 2025
Predictors of depression among Chinese college students: a machine learning approach.
Depression in Chinese college students: key predictors identified through machine learning. Factors include anxiety, sleep quality, and gender differences. ππ§
February 7, 2025