A Deep Learning Model Based on MRI and Clinical Factors Facilitates Noninvasive Evaluation of KRAS Mutation in Rectal Cancer
Author:
Affiliation:
1. Department of Radiology Xinhua Hospital, Shanghai Jiao Tong University School of Medicine Shanghai China
2. Institute of Advanced Research Infervision Medical Technology Co., Ltd Beijing China
Funder
National Natural Science Foundation of China
Publisher
Wiley
Subject
Radiology, Nuclear Medicine and imaging
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/jmri.28237
Reference43 articles.
1. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries
2. Analysis of KRAS , NRAS , BRAF , PIK3CA and TP53 mutations in a large prospective series of locally advanced rectal cancer patients
3. Impact of KRAS status on tumor response and survival after neoadjuvant treatment of locally advanced rectal cancer
4. 18F-FDG PET/CT imaging in rectal cancer: relationship with theRASmutational status
5. Multicenter Randomized Phase II Clinical Trial Comparing Neoadjuvant Oxaliplatin, Capecitabine, and Preoperative Radiotherapy With or Without Cetuximab Followed by Total Mesorectal Excision in Patients With High-Risk Rectal Cancer (EXPERT-C)
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1. Artificial Intelligence Applications in the Treatment of Colorectal Cancer: A Narrative Review;Clinical Medicine Insights: Oncology;2024-01
2. Deep Learning‐Based Multiparametric MRI Model for Preoperative T‐Stage in Rectal Cancer;Journal of Magnetic Resonance Imaging;2023-06-27
3. Development and validation of a stacking nomogram for predicting regional lymph node metastasis status in rectal cancer via deep learning and hand-crafted radiomics;INT J RADIAT RES;2023
4. Editorial for “A Deep Learning Model Based on MRI and Clinical Factors Facilitates Noninvasive Prediction of KRAS Mutation in Rectal Cancer”;Journal of Magnetic Resonance Imaging;2022-05-16
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