Machine learning prediction of germline BRCA1/2 pathogenic variants in patients with ovarian cancer

Objectives To assess the performance of machine learning (ML) algorithms to predict the presence of germline BRCA1/2 pathogenic variants in ovarian cancer (OC) patients based on clinical–pathological features.Methods Clinical–pathological features of 648 patients with OC tested for BRCA1/2 were anal...

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Главные авторы:	Pierandrea De Iaco, Anna Myriam Perrone, Antonio De Leo, Paola Rucci, Daniela Turchetti, Claudio Zamagni, Giovanni Innella, Lea Godino, Giulia Erini, Simona Ferrari, Sara Miccoli, Luca Caramanna
Формат:	Artigo
Язык:	Inglês
Опубликовано:	BMJ Publishing Group 2025-12-01
Серии:	BMJ Health & Care Informatics
Online-ссылка:	https://informatics.bmj.com/content/32/1/e101751.full
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