Evaluating the Predictive Accuracy of Models for Mortality in Internal and External Validation Cohorts.

Evaluating the Predictive Accuracy of Models for Mortality in Internal and External Validation Cohorts.

<p>Evaluating the Predictive Accuracy of Models for Mortality in Internal and External Validation Cohorts.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Lanyue Pan (16035014) (author)
مؤلفون آخرون:	Chunmei Wu (3202050) (author), Ping Li (31981) (author), Jiaquan Huang (118392) (author), Yizhi Wu (210380) (author), Guo Li (174860) (author)
منشور في:	2025
الموضوعات:	Medicine Biotechnology Cancer Science Policy Infectious Diseases Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified serum total bilirubin receiver operating characteristic less common subtypes integrated discrimination improvement highest c statistic higher c statistic hepatitis b co heavy economic burden demonstrated good performance colonic tumoroid proliferation aid clinical decision risk factors associated akaike information criterion external cohort consisted sixteen candidate variables formulating patient follow excluding 17 patients ascites occurrence frequency variable model showed external validation cohort alt ), albumin three simpler models year mortality outcome cause mortality rate roc curves indicated variable model simpler models cause mortality mortality rate three groups internal validation increased risk hbsag ), incomplete information reduced models multivariate model model predicting different models derivation cohort xlink "> term prognosis splenectomy history roc curves randomly assigned predictive value predictive tools personalized follow nutritional status lowest aic large population
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