Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics-Reference-Cited by-同舟云学术

Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics

Published:2022-04 Issue: Volume:46 Page:101380
ISSN:2589-5370
Container-title:eClinicalMedicine
language:en
Short-container-title:eClinicalMedicine

Author:

Fang Mengjie,Tian Jie,Dong Di^ORCID

Publisher

Elsevier BV

Subject

General Medicine

Reference10 articles.

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2. Advanced gastric cancer: CT radiomics prediction and early detection of downstaging with neoadjuvant chemotherapy;Xu;Eur Radiol,2021

3. Computed tomography-based radiomics for prediction of neoadjuvant chemotherapy outcomes in locally advanced gastric cancer: a pilot study;Li;Chin J Cancer Res,2018

4. A CT-based deep learning radiomics nomogram for predicting the response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer: a multicenter cohort study;eClinicalMedicine,2022

5. Histopathologic diversity of gastric cancers: relationship between enhancement pattern on dynamic contrast-enhanced CT and histological type;Tsurumaru;Eur J Radiol,2017

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