Prediction of prostate biopsy outcomes at different cut-offs of prostate-specific antigen using machine learning: a multicenter study

Abstract Background Machine learning (ML) is a significant area of artificial intelligence, which can improve the accuracy of predictive or diagnostic models for differentiating between prostate biopsy outcomes. This study aims to develop a novel decision-support ML model for classifying patients wi...

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Главные авторы:	Mostafa A. Arafa, Karim H. Farhat, Sherin F. Aly, Farrukh K. Khan, Alaa Mokhtar, Abdulaziz M. Althunayan, Waleed Al-Taweel, Sultan S. Al-Khateeb, Sami Azhari, Danny M. Rabah
Формат:	Artigo
Язык:	Inglês
Опубликовано:	SpringerOpen 2025-03-01
Серии:	Journal of the Egyptian National Cancer Institute
Предметы:	Machine learning prediction models Prostate biopsy outcomes Prostate-specific antigen cut-offs
Online-ссылка:	https://doi.org/10.1186/s43046-025-00265-3
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