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 study of 77 developed and developing nations finds that digital transformation is associated with a reduced ecological footprint, with ...
A retrospective cohort study evaluated baseline clinical, virological, and fibrosis-related predictors of direct-acting antiviral failure in adults with concurrent hepatitis ...
A machine-learning model utilizing routine laboratory indicators demonstrated strong predictive performance for nasopharyngeal carcinoma across multicenter cohorts.
Researchers evaluated multiple machine learning algorithms using NHANES survey data from 2005 to 2020, finding that a random forest model ...
A deep learning framework using Swin Transformer feature extraction and feature selection achieved 98.31 percent accuracy in diagnosing multi-class skin ...
A hybrid framework pairing ant colony feature selection with grey wolf classifier tuning detected epileptic seizures across benchmark multichannel EEG ...
Researchers mapped regional landslide susceptibility across Uttarakhand's Uttarkashi District using ensemble machine learning models that achieved area under the curve ...
In a retrospective study of 270 patients with DWI-negative transient ischemic attack, machine learning models showed moderate discrimination for 30-day ...
A new study uses machine learning to predict hospital stay duration after discectomy, identifying key clinical and surgical factors that ...
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© 2026 Scienmag - Science Magazine