Sticking to an exercise routine is a challenge many people face. But a research team is using machine learning to uncover what keeps individuals committed to their workouts. Sticking to an exercise ...
A machine learning-driven framework accurately predicts MPA exposure and supports individualized dosing in childhood-onset LN.
A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...
Using a real-world, nationwide electronic health record–derived deidentified database of 38,048 patients with advanced NSCLC, we trained binary prediction algorithms to predict likelihood of 12-month ...
Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits and suddenly, a molecule makes a promising new medicine. Normally, creating better ...
A total of 590 patients were identified, 432 in the development set and 158 in the validation set. The median age was 51 years, and 55.8% (329 of 590) experienced grade 3 or 4 toxicity. The ...
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Using AI to predict earthquakes: Machine learning detects subtle changes before lab-scale fault failures
Predicting earthquakes has long been an unattainable fantasy. Factors like odd animal behaviors that have historically been thought to forebode earthquakes are not supported by empirical evidence. As ...
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Machine learning can predict patients' responses to antidepressants while disentangling drug and placebo effects
Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global population. It is characterized by a persistent low mood, disruptions in typical ...
A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...
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