Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...
A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.
Ionospheric delay remains a significant error source in GNSS positioning, particularly for single-frequency users and during periods of enhanced space weather ...
Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...
MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...
Artificial intelligence applied to the ECG is expanding the clinical role of this widely available diagnostic tool beyond ...
From Stock-to-Flow and Power Law to NVT ratios and machine learning, the most common crypto prediction models each carry ...
UTokyo and Kubota develop a drone potato yield prediction method combining multispectral imagery, AI, and growth models.
Three heads are better than one. Versions of this proverb are found worldwide and throughout history. Yet in the race to ...
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