Predicting Treatment Response to Intra-arterial Therapies of Hepatocellular Carcinoma using Supervised Machine Learning—An Artificial Intelligence Concept

PURPOSE: To use magnetic resonance (MR) imaging and clinical patient data to create an artificial intelligence (AI) framework for the prediction of therapeutic outcomes of trans-arterial chemoembolization (TACE) by applying machine learning (ML) techniques. METHODS: This study included 36 patients w...

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Detaylı Bibliyografya
Yayımlandı:J Vasc Interv Radiol
Asıl Yazarlar: Abajian, Aaron, Murali, Nikitha, Savic, Lynn Jeanette, Laage-Gaupp, Fabian Max, Nezami, Nariman, Duncan, James S., Schlachter, Todd, Lin, MingDe, Geschwind, Jean-François, Chapiro, Julius
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: 2018
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Article
Online Erişim:https://ncbi.nlm.nih.gov/pmc/articles/PMC5970021/
https://ncbi.nlm.nih.gov/pubmed/29548875
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jvir.2018.01.769
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