A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer

A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer

Abstract Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to identify a set of molecular markers for predicting platinum sensitivity. A signature predicting cisplatin sensitivity was generated using the Ge...

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Autores principales: Nicholas Brian Shannon, Laura Ling Ying Tan, Qiu Xuan Tan, Joey Wee-Shan Tan, Josephine Hendrikson, Wai Har Ng, Gillian Ng, Ying Liu, Xing-Yi Sarah Ong, Ravichandran Nadarajah, Jolene Si Min Wong, Grace Hwei Ching Tan, Khee Chee Soo, Melissa Ching Ching Teo, Claramae Shulyn Chia, Chin-Ann Johnny Ong
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Medicine
R
Science
Q
Acceso en línea:https://doaj.org/article/0247321c07774b35a5929fc1ffdacadd
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https://doaj.org/article/0247321c07774b35a5929fc1ffdacadd

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