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...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9521878/ |