Machine studying (ML) fashions predict in-hospital mortality in intensive care unit (ICU) sufferers with lymphoma, in line with a examine printed on-line Aug. 20 in PLOS ONE.
Ling Xu, from the Guangzhou College of Conventional Chinese language Medication in Dongguan, China, and colleagues developed and validated ML fashions to foretell in-hospital mortality in grownup ICU sufferers with lymphoma in a retrospective cohort examine utilizing knowledge from the Medical Info Mart for Intensive Care IV database. Fifteen machine studying fashions had been developed and in contrast utilizing receiver working attribute curves and an space beneath the curve (AUC) evaluation.
The analyses included 1,591 sufferers, with 342 (21.5%) in-hospital deaths. The researchers discovered that Lasso regression recognized important predictors of mortality, together with blood urea nitrogen (BUN), platelets, prothrombin time (PT), coronary heart price, systolic blood stress, activated partial thromboplastin time, oxygen saturation, and bicarbonate.
The very best predictive efficiency was seen for the CatBoost classifier, with an AUC of 0.7766. The important function of BUN was highlighted in a SHapley Additive exPlanation (SHAP) evaluation, which was crucial think about mortality prediction, adopted by platelets and PT. Individualized threat assessments had been offered by the SHAP pressure plot, demonstrating the flexibility of the mannequin to determine high-risk subgroups.
“The ML models, particularly the CatBoost Classifier, may assist in risk estimation of in-hospital mortality among ICU patients with lymphoma,” the authors write. “These models not only offer additional insights alongside traditional approaches but also provide interpretable risk assessments through SHAP value analysis.”
Extra info:
Ling Xu et al, Predicting in-hospital mortality in ICU sufferers with lymphoma utilizing machine studying fashions, PLOS One (2025). DOI: 10.1371/journal.pone.0330197
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AI fashions can assist predict in-hospital mortality in ICU sufferers with lymphoma (2025, August 29)
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