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AI trained on sleep data predicts future disease and mortality years in advance
The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology We used an innovative machine learning approach to analyze ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Machine learning algorithms utilizing electronic health records can effectively predict two-year dementia risk among American Indian/Alaska Native adults aged 65 years and older, according to a ...
A recent study by Yale researchers demonstrated the potential of a machine learning approach to predict symptoms of post-traumatic stress disorder, or PTSD, for recent trauma survivors. Researchers ...
DailyGuide Network on MSN
Machine learning weather models are transforming climate forecasting across Africa
The Writer As climate extremes intensify across Africa, the need for accurate and timely weather prediction has become ...
IEEE Spectrum on MSN
Machine learning system monitors patient pain during surgery
To create their contactless approach, the researchers created a machine learning algorithm capable of analyzing aspects of ...
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