Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics.
作者信息
Fang Mengjie, Tian Jie, Dong Di
机构信息
School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.
CAS Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Beijing Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, No.95 Zhongguancun East Road, Beijing 100190, China.
出版信息
EClinicalMedicine. 2022 Apr 7;46:101380. doi: 10.1016/j.eclinm.2022.101380. eCollection 2022 Apr.
Abstract
摘要
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本文引用的文献
1
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.基于CT的深度学习影像组学列线图预测局部晚期胃癌患者新辅助化疗反应：一项多中心队列研究
EClinicalMedicine. 2022 Mar 21;46:101348. doi: 10.1016/j.eclinm.2022.101348. eCollection 2022 Apr.
2
Advanced gastric cancer: CT radiomics prediction and early detection of downstaging with neoadjuvant chemotherapy.晚期胃癌：CT 放射组学预测及新辅助化疗降期的早期检测。
Eur Radiol. 2021 Nov;31(11):8765-8774. doi: 10.1007/s00330-021-07962-2. Epub 2021 Apr 28.
3
Identifying early gastric cancer under magnifying narrow-band images with deep learning: a multicenter study.基于深度学习的放大窄带成像识别早期胃癌：多中心研究。
Gastrointest Endosc. 2021 Jun;93(6):1333-1341.e3. doi: 10.1016/j.gie.2020.11.014. Epub 2020 Nov 26.
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Gastric cancer.胃癌。
Lancet. 2020 Aug 29;396(10251):635-648. doi: 10.1016/S0140-6736(20)31288-5.
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Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study.深度学习放射组学列线图可预测局部进展期胃癌的淋巴结转移数目：一项国际多中心研究。
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