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A Comparison Study of Machine Learning (Random Survival Forest) and Classic Statistic (Cox Proportional Hazards) for Predicting Progression in High-Grade Glioma after Proton and Carbon Ion Radiotherapy
Research article (Frontiers in Oncology, 2020) · cited 75× · AI/ML
A Comparison Study of Machine Learning (Random Survival Forest) and Classic Statistic (Cox Proportional Hazards) for Predicting Progression in High-Grade Glioma after Proton and Carbon Ion Radiotherapy
Summary
A Comparison Study of Machine Learning (Random Survival Forest) and Classic Statistic (Cox Proportional Hazards) for Predicting Progression in High-Grade Glioma after Proton and Carbon Ion Radiotherapy is a scholarly article[1].
Key Facts
A Comparison Study of Machine Learning (Random Survival Forest) and Classic Statistic (Cox Proportional Hazards) for Predicting Progression in High-Grade Glioma after Proton and Carbon Ion Radiotherapy's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). A Comparison Study of Machine Learning (Random Survival Forest) and Classic Statistic (Cox Proportional Hazards) for Predicting Progression in High-Grade Glioma after Proton and Carbon Ion Radiotherapy. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-comparison-study-of-machine-learning-random-survival-forest-and-classic-statistic-cox-proportional-hazards-for-predict
MLA“A Comparison Study of Machine Learning (Random Survival Forest) and Classic Statistic (Cox Proportional Hazards) for Predicting Progression in High-Grade Glioma after Proton and Carbon Ion Radiotherapy.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-comparison-study-of-machine-learning-random-survival-forest-and-classic-statistic-cox-proportional-hazards-for-predict.
BibTeX@misc{4ortxyz_a-comparison-study-of-machine-learning-random-survival-forest-and-classic-statistic-cox-proportional-hazards-for-predict_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A Comparison Study of Machine Learning (Random Survival Forest) and Classic Statistic (Cox Proportional Hazards) for Predicting Progression in High-Grade Glioma after Proton and Carbon Ion Radiotherapy}}, year = {2026}, url = {https://4ort.xyz/entity/a-comparison-study-of-machine-learning-random-survival-forest-and-classic-statistic-cox-proportional-hazards-for-predict}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A Comparison Study of Machine Learning (Random Survival Forest) and Classic Statistic (Cox Proportional Hazards) for Predicting Progression in High-Grade Glioma after Proton and Carbon Ion Radiotherapy — https://4ort.xyz/entity/a-comparison-study-of-machine-learning-random-survival-forest-and-classic-statistic-cox-proportional-hazards-for-predict (retrieved 2026-05-24)
