The Use of Artificial Intelligence in Predicting Chemotherapy-Induced Toxicities in Metastatic Colorectal Cancer: A Data-Driven Approach for Personalized Oncology

Background: Machine learning models learn about general behavior from data by finding the relationships between features. Our purpose was to develop a predictive model to identify and predict which subset of colorectal cancer patients are more likely to experience chemotherapy-induced toxicity and t...

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Bibliografische Detailangaben

Hauptverfasser:	Eliza-Maria Froicu, Oriana-Maria Oniciuc, Vlad-Adrian Afrăsânie, Mihai-Vasile Marinca, Silvia Riondino, Elena Adriana Dumitrescu, Teodora Alexa-Stratulat, Iulian Radu, Lucian Miron, Gema Bacoanu, Vladimir Poroch, Bogdan Gafton
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2024-09-01
Schriftenreihe:	Diagnostics
Schlagworte:	metastatic colorectal cancer artificial intelligence prediction model chemotherapy toxicity
Online-Zugang:	https://www.mdpi.com/2075-4418/14/18/2074
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