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1 Ergebnisse
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HIV Progression and Outcome Prediction to Enhance Patient M..:
, In:
2024 IEEE 14th Annual Computing and Communication Workshop and Conference (CCWC)
,
Mahto, Rakeshkumar
;
Sood, Kanika
- p. 0278-0284 , 2024
Link:
https://doi.org/10.1109/CCWC60891.2024.10427778
RT T1 <cTitle>2024 IEEE 14th Annual Computing and Communication Workshop and Conference (CCWC)</cTitle>: T1 <Title>HIV Progression and Outcome Prediction to Enhance Patient Matching for Clinical Trials</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10427778&Exemplar=1&LAN=DE A1 Mahto, Rakeshkumar A1 Sood, Kanika YR 2024 K1 Support vector machines K1 Predictive models K1 Clinical trials K1 Prediction algorithms K1 Boosting K1 Human immunodeficiency virus K1 Random forests K1 Random forest K1 HIV K1 gradient boosting methods (XGBoost) K1 support vector machine (SVM) K1 machine learning (ML) K1 naïve bayes (NB) K1 logistic regression SP 0278 OP 0284 LK http://dx.doi.org/https://doi.org/10.1109/CCWC60891.2024.10427778 DO https://doi.org/10.1109/CCWC60891.2024.10427778 SF ELIB - SuUB Bremen
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