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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Preoperative prediction of KRAS mutation status in colorectal cancer using a CT-based radiomics nomogram
Ting Xue, Hui Peng, Qiaoling Chen, et al.
British Journal of Radiology (2022) Vol. 95, Iss. 1134
Open Access | Times Cited: 19

Showing 19 citing articles:

Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics
Ramy Abou Ghayda, Rossella Cannarella, Aldo E. Calogero, et al.
The World Journal of Men s Health (2023) Vol. 42, Iss. 1, pp. 39-39
Open Access | Times Cited: 32
Current status and quality of radiomic studies for predicting KRAS mutations in colorectal cancer patients: A systematic review and meta‑analysis
Lulu Jia, Jian-Xin Zhao, Lianping Zhao, et al.
European Journal of Radiology (2022) Vol. 158, pp. 110640-110640
Open Access | Times Cited: 24
Role of Machine Learning in Precision Oncology: Applications in Gastrointestinal Cancers
Azadeh Tabari, Shin Mei Chan, Omar M. Omar, et al.
Cancers (2022) Vol. 15, Iss. 1, pp. 63-63
Open Access | Times Cited: 23
Digital Medical X-ray Imaging, CAD in Lung Cancer and Radiomics in Colorectal Cancer: Past, Present and Future
Jacobo Porto-Álvarez, Gary T. Barnes, Alex Villanueva, et al.
Applied Sciences (2023) Vol. 13, Iss. 4, pp. 2218-2218
Open Access | Times Cited: 14
Artificial intelligence applied to the diagnosis of colorectal cancer
Ana Jiménez-Pastor, Carmen Prieto-de-la-Lastra
Elsevier eBooks (2025), pp. 249-260
Closed Access
Construction and Value Analysis of a Prognostic Assessment Model Based on Radiomics and Genetic Data for Colorectal Cancer
Yongna Cheng, Zi‐Ming Feng, Xiangming Wang
British Journal of Hospital Medicine (2025) Vol. 86, Iss. 3, pp. 1-18
Closed Access
CT-based radiomics nomogram for the preoperative prediction of microsatellite instability and clinical outcomes in colorectal cancer: a multicentre study
Ming Li, Gang Xu, Yang Cui, et al.
Clinical Radiology (2023) Vol. 78, Iss. 10, pp. e741-e751
Closed Access | Times Cited: 9
Improving prediction of treatment response and prognosis in colorectal cancer with AI-based medical image analysis
Xiangyu Liu, Song Zhang, Lizhi Shao, et al.
The Innovation Medicine (2024) Vol. 2, Iss. 2, pp. 100069-100069
Open Access | Times Cited: 3
Role of radiomics in the diagnosis and treatment of gastrointestinal cancer
Qi Mao, Mao-Ting Zhou, Zhang-Ping Zhao, et al.
World Journal of Gastroenterology (2022) Vol. 28, Iss. 42, pp. 6002-6016
Open Access | Times Cited: 14
CHNet: A multi-task global–local Collaborative Hybrid Network for KRAS mutation status prediction in colorectal cancer
Meiling Cai, Lin Zhao, Yan Qiang, et al.
Artificial Intelligence in Medicine (2024) Vol. 155, pp. 102931-102931
Closed Access | Times Cited: 1
Exploring the value of multiple preprocessors and classifiers in constructing models for predicting microsatellite instability status in colorectal cancer
Yi Ma, Zhihao Shi, Ying Wei, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Computed Tomography-based Radiomics Nomogram for the Preoperative Prediction of Tumor Deposits and Clinical Outcomes in Colon Cancer: a Multicenter Study
Manman Li, Guodong Xu, Qiaoling Chen, et al.
Academic Radiology (2022) Vol. 30, Iss. 8, pp. 1572-1583
Closed Access | Times Cited: 7
Computed tomography-based radiomics nomogram for the pre-operative prediction of BRAF mutation and clinical outcomes in patients with colorectal cancer: a double-center study
Manman Li, Guodong Xu, Hui Zhou, et al.
British Journal of Radiology (2023) Vol. 96, Iss. 1148
Closed Access | Times Cited: 3
A Contrast-Enhanced CT-Based Deep Learning System for Preoperative Prediction of Colorectal Cancer Staging and RAS Mutation
Na Lü, Xiao Guan, Zhu Jian-guo, et al.
Cancers (2023) Vol. 15, Iss. 18, pp. 4497-4497
Open Access | Times Cited: 2
The potential of artificial intelligence and machine learning in precision oncology
Adhari AlZaabi, Yassine Bouchareb, Layth Mula‐Hussain
Elsevier eBooks (2024), pp. 173-188
Closed Access
Construction of Colorectal Cancer Prognostic Model Based on Radiomics
永娜 程
Advances in Clinical Medicine (2024) Vol. 14, Iss. 09, pp. 1317-1333
Closed Access
Prediction of myocardial ischemia in coronary heart disease patients using a CCTA–Based radiomic nomogram
Youchang Yang, Yang Dou, Zhiwei Wang, et al.
Frontiers in Cardiovascular Medicine (2023) Vol. 10
Open Access
Radiomics biomarkers are associated with survival in patients with Oesophageal Adenocarcinoma
Lauren G. Aoude, Bernadette Z.Y. Wong, Vanessa Bonazzi, et al.
Research Square (Research Square) (2023)
Open Access
Important parameters should be paid attention in PTMC radiofrequency ablation
Yiping Dong, Yanling Cheng, Peile Jin, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access
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