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MACHINE LEARNING--BASED PREDICTION OF CHEMOTHERAPY TOXICITY IN COLORECTAL CANCER: A PERSONALIZED RISK STRATIFICATION APPROACH.

Background: Machine learning models learn feature connections from data to learn general behavior. The goal was to build a prediction model to identify the percentage of patients with colorectal cancer who are at increased risk of chemotherapy-induced toxicity and to determine the factors that affec...

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Published in:Scientific Culture Vol. 12; no. 5 Part 1; pp. 942 - 953
Main Author: Rajendran, Ohmini Krishnamurthy
Format: Article
Published: University of the Aegean 2026
Subjects:
Chemotherapy complications
Colorectal cancer
Artificial intelligence
Individualized medicine
Risk assessment
Random forest algorithms
Machine learning
Prediction models
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