Machine learning approaches to the human metabolome in sepsis identify metabolic links with survival

Abstract Background Metabolic predictors and potential mediators of survival in sepsis have been incompletely characterized. We examined whether machine learning (ML) tools applied to the human plasma metabolome could consistently identify and prioritize metabolites implicated in sepsis survivorship...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:Intensive Care Medicine Experimental
المؤلفون الرئيسيون: Leah B. Kosyakovsky, Emily Somerset, Angela J. Rogers, Michael Sklar, Jared R. Mayers, Augustin Toma, Yishay Szekely, Sabri Soussi, Bo Wang, Chun-Po S. Fan, Rebecca M. Baron, Patrick R. Lawler
التنسيق: مقال
اللغة:الإنجليزية
منشور في: SpringerOpen 2022-06-01
الموضوعات:
Artificial intelligence
Machine learning
Metabolism
Metabolomics
Sepsis
الوصول للمادة أونلاين:https://doi.org/10.1186/s40635-022-00445-8

الانترنت

https://doi.org/10.1186/s40635-022-00445-8

مواد مشابهة