A Machine Learning Model to Predict Hepatocellular Carcinoma Response to Transcatheter Arterial Chemoembolization

PURPOSE: To evaluate a fully automated machine learning algorithm that uses pretherapeutic quantitative CT image features and clinical factors to predict hepatocellular carcinoma (HCC) response to transcatheter arterial chemoembolization (TACE). MATERIALS AND METHODS: Outcome information from 105 pa...

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Veröffentlicht in:Radiol Artif Intell
Hauptverfasser: Morshid, Ali, Elsayes, Khaled M., Khalaf, Ahmed M., Elmohr, Mohab M., Yu, Justin, Kaseb, Ahmed O., Hassan, Manal, Mahvash, Armeen, Wang, Zhihui, Hazle, John D., Fuentes, David
Format: Artigo
Sprache:Inglês
Veröffentlicht: Radiological Society of North America 2019
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Original Research
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6920060/
https://ncbi.nlm.nih.gov/pubmed/31858078
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryai.2019180021
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