Machine learning for grading and prognosis of esophageal dysplasia using mass spectrometry and histological imaging-Reference-Cited by-同舟云学术

Machine learning for grading and prognosis of esophageal dysplasia using mass spectrometry and histological imaging

Published:2021-11 Issue: Volume:138 Page:104918
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Beuque Manon,Martin-Lorenzo Marta^ORCID,Balluff Benjamin^ORCID,Woodruff Henry C.^ORCID,Lucas Marit,de Bruin Daniel M.,van Timmeren Janita E.,Boer Onno J.de,Heeren Ron MA.^ORCID,Meijer Sybren L.,Lambin Philippe

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference21 articles.

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4. Barrett's oesophagus patients with low-grade dysplasia can be accurately risk-stratified after histological review by an expert pathology panel;Duits;Gut,2015

5. Evaluation of dysplasia in Barrett esophagus;Gross;Gastroenterol. Hepatol.,2018

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