Literature DB >> 32076661

From Code to Bedside: Introducing Predictive Intelligence to Interventional Oncology.

Julius Chapiro1, James S Duncan1.   

Abstract

Entities:  

Year:  2019        PMID: 32076661      PMCID: PMC6776876          DOI: 10.1148/ryai.2019190139

Source DB:  PubMed          Journal:  Radiol Artif Intell        ISSN: 2638-6100


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  6 in total

Review 1.  EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma.

Authors: 
Journal:  J Hepatol       Date:  2018-04-05       Impact factor: 25.083

2.  Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning-An Artificial Intelligence Concept.

Authors:  Aaron Abajian; Nikitha Murali; Lynn Jeanette Savic; Fabian Max Laage-Gaupp; Nariman Nezami; James S Duncan; Todd Schlachter; MingDe Lin; Jean-François Geschwind; Julius Chapiro
Journal:  J Vasc Interv Radiol       Date:  2018-03-14       Impact factor: 3.464

3.  A machine learning model to predict hepatocellular carcinoma response to transcatheter arterial chemoembolization.

Authors:  Ali Morshid; Khaled M Elsayes; Ahmed M Khalaf; Mohab M Elmohr; Justin Yu; Ahmed O Kaseb; Manal Hassan; Armeen Mahvash; Zhihui Wang; John D Hazle; David Fuentes
Journal:  Radiol Artif Intell       Date:  2019-09-25

4.  Global patterns of hepatocellular carcinoma management from diagnosis to death: the BRIDGE Study.

Authors:  Joong-Won Park; Minshan Chen; Massimo Colombo; Lewis R Roberts; Myron Schwartz; Pei-Jer Chen; Masatoshi Kudo; Philip Johnson; Samuel Wagner; Lucinda S Orsini; Morris Sherman
Journal:  Liver Int       Date:  2015-03-25       Impact factor: 5.828

5.  Deep learning cardiac motion analysis for human survival prediction.

Authors:  Ghalib A Bello; Timothy J W Dawes; Jinming Duan; Carlo Biffi; Antonio de Marvao; Luke S G E Howard; J Simon R Gibbs; Martin R Wilkins; Stuart A Cook; Daniel Rueckert; Declan P O'Regan
Journal:  Nat Mach Intell       Date:  2019-02-11
  6 in total

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