Gradient Boosting Model Predicts Low Birth Weight in Retrospective Singleton Study
A retrospective cohort study of 4,498 singleton pregnancies found that a gradient boosting machine model using early clinical indicators accurately ...
A retrospective cohort study of 4,498 singleton pregnancies found that a gradient boosting machine model using early clinical indicators accurately ...
A neural network model showed promising discrimination for predicting in-hospital mortality after surgery in male patients with acute type A ...
A dual-center study revealed the triglyceride-glucose index predicted new-onset cardiovascular events in elderly coronary heart disease patients more effectively than ...
A retrospective study shows that contrast-enhanced CT deep learning and habitat radiomics models effectively differentiate common pathological subtypes of small ...
A new risk screening model validated in 552 older patients identifies ten key factors for predicting frailty in those with ...
An exploratory study of 67 systemic sclerosis patients found that machine learning models built from HRCT radiomic features detected interstitial ...
Researchers have introduced a continuous net benefit metric that summarises the clinical utility of prediction models across a whole range ...
Researchers extend decision curve analysis to continuous endpoints, revealing how linearity assumptions and probability interpretations impact clinical utility.
A retrospective single-center study of 781 traumatic brain injury patients built a nomogram combining early chest CT ground-glass opacity and ...
A machine learning model combining CT radiomics with clinical variables predicted spontaneous ureteral stone passage within four weeks with an ...
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© 2026 Scienmag - Science Magazine