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:

Radiomics Approaches for the Prediction of Pathological Complete Response after Neoadjuvant Treatment in Locally Advanced Rectal Cancer: Ready for Prime Time?
Vincent Bourbonne, Ulrike Schick, Olivier Pradier, et al.
Cancers (2023) Vol. 15, Iss. 2, pp. 432-432
Open Access | Times Cited: 17

Showing 17 citing articles:

An automated deep learning pipeline for EMVI classification and response prediction of rectal cancer using baseline MRI: a multi-centre study
Lishan Cai, Doenja M. J. Lambregts, Geerard L. Beets, et al.
npj Precision Oncology (2024) Vol. 8, Iss. 1
Open Access | Times Cited: 9

Preoperative prediction of perineural invasion of rectal cancer based on a magnetic resonance imaging radiomics model: A dual-center study
Yan Liu, Bai-Jin-Tao Sun, Chuan Zhang, et al.
World Journal of Gastroenterology (2024) Vol. 30, Iss. 16, pp. 2233-2248
Open Access | Times Cited: 6

Pretreatment Pan-Immune-Inflammation Value (PIV) in Predicting Therapeutic Response and Clinical Outcomes of Neoadjuvant Immunochemotherapy for Esophageal Squamous Cell Carcinoma
Ji‐Feng Feng, Liang Wang, Xun Yang, et al.
Annals of Surgical Oncology (2023) Vol. 31, Iss. 1, pp. 272-283
Closed Access | Times Cited: 13

Radiomics in rectal cancer: current status of use and advances in research
Weiqin Huang, Rongbo Lin, Ke Xu, et al.
Frontiers in Oncology (2025) Vol. 14
Open Access

Selection of rectal cancer patients for organ preservation after neoadjuvant therapy: value of T2W-MRI signal intensity
Denise J. van der Reijd, Xinde Ou, Rebecca A.P. Dijkhoff, et al.
Acta Radiologica (2025)
Closed Access

Integration of Radiomics and Tumor Biomarkers in Interpretable Machine Learning Models
Lennart Brocki, Neo Christopher Chung
Cancers (2023) Vol. 15, Iss. 9, pp. 2459-2459
Open Access | Times Cited: 7

Application research of radiomics in colorectal cancer: A bibliometric study
Lihong Yang, Binjie Wang, Xiaoying Shi, et al.
Medicine (2024) Vol. 103, Iss. 15, pp. e37827-e37827
Open Access | Times Cited: 2

Can Pretreatment MRI and Planning CT Radiomics Improve Prediction of Complete Pathological Response in Locally Advanced Rectal Cancer Following Neoadjuvant Treatment?
Jeba Karunya Ramireddy, Anvitha Sathya, Balu Krishna Sasidharan, et al.
Journal of Gastrointestinal Cancer (2024) Vol. 55, Iss. 3, pp. 1199-1211
Closed Access | Times Cited: 1

Nonoperative Management of dMMR/MSI-H Colorectal Cancer following Neoadjuvant Immunotherapy: A Narrative Review
Binyi Xiao, Jiehai Yu, Peirong Ding
Clinics in Colon and Rectal Surgery (2023) Vol. 36, Iss. 06, pp. 378-384
Open Access | Times Cited: 2

Radiomics from Mesorectal Blood Vessels and Lymph Nodes: A Novel Prognostic Predictor for Rectal Cancer with Neoadjuvant Therapy
Siyuan Qin, Siyi Lu, Ke Liu, et al.
Diagnostics (2023) Vol. 13, Iss. 12, pp. 1987-1987
Open Access | Times Cited: 2

Development and validation of a competitive risk model in patients with rectal cancer: based on SEER database
Ruo‐Bing Hu, Xiuling Li, Xiaomin Zhou, et al.
European journal of medical research (2023) Vol. 28, Iss. 1
Open Access | Times Cited: 1

A Novel Effectiveness Assessment Framework for Neoadjuvant Chemoradiotherapy of Locally Advanced Rectal Cancer Based on Multi-modal Intelligence
Xiao Tian, Dong Sui, Weifeng Liu, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2023), pp. 1-6
Closed Access

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