Precision-Recall curves comparing 7 machine learning models and a baseline value.

Precision-Recall curves comparing 7 machine learning models and a baseline value.

<p>PR curves are computed using the withheld test data. SVM is the model with the highest area under the curve.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Andres Portocarrero-Bonifaz (21367929) (author)
مؤلفون آخرون:	Salman Syed (18880470) (author), Maxwell Kassel (21367932) (author), Grant W. McKenzie (21367935) (author), Vishwa M. Shah (21367938) (author), Bryce M. Forry (21367941) (author), Jeremy T. Gaskins (9281129) (author), Keith T. Sowards (21367944) (author), Thulasi Babitha Avula (21367947) (author), Adrianna Masters (21367950) (author), Jose G. Schneider (21367953) (author), Scott R. Silva (14975143) (author)
منشور في:	2025
الموضوعات:	Biotechnology Cancer Infectious Diseases Virology Biological Sciences not elsewhere classified Information Systems not elsewhere classified without grade 3 support vector machines rectum differed significantly predicting grade 3 predict grade 3 normmcc testing scores gaussian naive bayes f1 testing scores external beam radiotherapy charlson comorbidity index applying exclusion criteria achieving satisfactory performance accuracy testing scores deep learning networks creating multivariable models final model performance machine learning presents predict patient outcomes advancing patient care machine learning models traditional statistical analysis predict specific toxicities high dose rate gynecological cancer patients underwent hdr brachytherapy machine learning applied models ranking model xlink "> women worldwide toxicity data retrospective analysis recent studies random forest prevalent cancers ovoid applicators often used novel solution nearest neighbors logistic regression hyperparameter tuning higher toxicities dosimetric variables data availability characterized using 233 patients
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