Machine Learning for Prediction of Survival Outcomes with Immune-Checkpoint Inhibitors in Urothelial Cancer

Machine Learning for Prediction of Survival Outcomes with Immune-Checkpoint Inhibitors in Urothelial Cancer

Machine learning (ML) may enhance the efficiency of developing accurate prediction models for survival, which is critical in informing disease prognosis and care planning. This study aimed to develop an ML prediction model for survival outcomes in patients with urothelial cancer-initiating atezolizu...

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Bibliographic Details
Main Authors: Ahmad Y. Abuhelwa, Ganessan Kichenadasse, Ross A. McKinnon, Andrew Rowland, Ashley M. Hopkins, Michael J. Sorich
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Cancers
Subjects:
machine learning
survival outcomes
immune checkpoint inhibitors
gradient boosting
random forest
Online Access:https://www.mdpi.com/2072-6694/13/9/2001

Internet

https://www.mdpi.com/2072-6694/13/9/2001

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