A Machine Learning-Aided Framework to Predict Outcomes of Anti-PD-1 Therapy for Patients With Gynecological Cancer on Incomplete Post-Marketing Surveillance Dataset

A Machine Learning-Aided Framework to Predict Outcomes of Anti-PD-1 Therapy for Patients With Gynecological Cancer on Incomplete Post-Marketing Surveillance Dataset

Post-marketing surveillance of antineoplastic agents is performed to evaluate the efficacy and safety in patients aiming at expanding drug indications and discovering potential adverse events. The real-world data is fraught with missing values. Literature addressing different strategies for dealing...

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Bibliographic Details
Main Authors: Xiaomei Liu, Zhifeng Xiao, Yang Song, Ruizhe Zhang, Xiuqin Li, Zhenhua Du
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Post-marketing surveillance
machine learning
gynecological cancer
Online Access:https://ieeexplore.ieee.org/document/9521878/

Internet

https://ieeexplore.ieee.org/document/9521878/

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