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Prediction of lung cancer risk at follow-up screening with low-dose CT: a training and validation study of a deep learning method.低剂量 CT 随访筛查中肺癌风险的预测:深度学习方法的训练和验证研究。
Lancet Digit Health. 2019 Nov;1(7):e353-e362. doi: 10.1016/S2589-7500(19)30159-1. Epub 2019 Oct 17.
2
From Local Explanations to Global Understanding with Explainable AI for Trees.利用可解释人工智能实现从局部解释到树木的全局理解
Nat Mach Intell. 2020 Jan;2(1):56-67. doi: 10.1038/s42256-019-0138-9. Epub 2020 Jan 17.
3
FOLFOX treatment response prediction in metastatic or recurrent colorectal cancer patients via machine learning algorithms.基于机器学习算法的转移性或复发性结直肠癌患者 FOLFOX 治疗反应预测。
Cancer Med. 2020 Feb;9(4):1419-1429. doi: 10.1002/cam4.2786. Epub 2020 Jan 1.
4
A Machine-Based Approach to Preoperatively Identify Patients with the Most and Least Benefit Associated with Resection for Intrahepatic Cholangiocarcinoma: An International Multi-institutional Analysis of 1146 Patients.一种基于机器的方法,用于术前识别与肝内胆管癌切除相关获益最多和获益最少的患者:来自 1146 例患者的国际多机构分析。
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Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging.深度学习从连续医学成像预测肺癌治疗反应。
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Machine Learning in Oncology: Methods, Applications, and Challenges.

作者信息

Bertsimas Dimitris, Wiberg Holly

机构信息

Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA.

Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA.

出版信息

JCO Clin Cancer Inform. 2020 Oct;4:885-894. doi: 10.1200/CCI.20.00072.

DOI:10.1200/CCI.20.00072
PMID:33058693
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7608565/
Abstract
摘要