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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:

Prognostic value of 18F-FDG PET/CT with texture analysis in patients with rectal cancer treated by surgery
Masatoshi Hotta, Ryogo Minamimoto, Yoshimasa Gohda, et al.
Annals of Nuclear Medicine (2021) Vol. 35, Iss. 7, pp. 843-852
Closed Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions
Nan Yang, Javier Del Ser, Simon Walsh, et al.
Information Fusion (2022) Vol. 82, pp. 99-122
Open Access | Times Cited: 101
Radiomics in colorectal cancer patients
Riccardo Inchingolo, Cesare Maino, Roberto Cannella, et al.
World Journal of Gastroenterology (2023) Vol. 29, Iss. 19, pp. 2888-2904
Open Access | Times Cited: 26
A review of harmonization strategies for quantitative PET
Go Akamatsu, Yuji Tsutsui, Hiromitsu Daisaki, et al.
Annals of Nuclear Medicine (2023) Vol. 37, Iss. 2, pp. 71-88
Open Access | Times Cited: 16
Impact of ComBat Harmonization on PET Radiomics-Based Tissue Classification: A Dual-Center PET/MRI and PET/CT Study
Doris Leithner, Heiko Schöder, Alexander Haug, et al.
Journal of Nuclear Medicine (2022) Vol. 63, Iss. 10, pp. 1611-1616
Open Access | Times Cited: 23
Four-dimensional quantitative analysis using FDG-PET in clinical oncology
Nagara Tamaki, Kenji Hirata, Tomoya Kotani, et al.
Japanese Journal of Radiology (2023) Vol. 41, Iss. 8, pp. 831-842
Open Access | Times Cited: 13
Artificial intelligence for nuclear medicine in oncology
Kenji Hirata, Hiroyuki Sugimori, Noriyuki Fujima, et al.
Annals of Nuclear Medicine (2022) Vol. 36, Iss. 2, pp. 123-132
Closed Access | Times Cited: 21
Prediction of Microsatellite Instability in Colorectal Cancer Using a Machine Learning Model Based on PET/CT Radiomics
Soyoung Kim, Jae‐Hoon Lee, Eun Jung Park, et al.
Yonsei Medical Journal (2023) Vol. 64, Iss. 5, pp. 320-320
Open Access | Times Cited: 11
Prediction by a multiparametric magnetic resonance imaging-based radiomics signature model of disease-free survival in patients with rectal cancer treated by surgery
Jiwei Mao, Wanli Ye, Weili Ma, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 4
Radiomic imaging: Basic principles and applications
Francesco Pisu, Luca Saba
Elsevier eBooks (2025), pp. 225-248
Closed Access
Position of the AI for Health Imaging (AI4HI) network on metadata models for imaging biobanks
Haridimos Kondylakis, Esther Ciarrocchi, Leonor Cerdá-Alberich, et al.
European Radiology Experimental (2022) Vol. 6, Iss. 1
Open Access | Times Cited: 15
Prediction of 5-year progression-free survival in advanced nasopharyngeal carcinoma with pretreatment PET/CT using multi-modality deep learning-based radiomics
Bingxin Gu, Mingyuan Meng, Lei Bi, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 15
Optimization and validation of 18F-DCFPyL PET radiomics-based machine learning models in intermediate- to high-risk primary prostate cancer
Wietske I. Luining, Daniela E. Oprea‐Lager, André N. Vis, et al.
PLoS ONE (2023) Vol. 18, Iss. 11, pp. e0293672-e0293672
Open Access | Times Cited: 7
The Usefulness of Machine Learning–Based Evaluation of Clinical and Pretreatment [18F]-FDG-PET/CT Radiomic Features for Predicting Prognosis in Hypopharyngeal Cancer
Masatoyo Nakajo, Kodai Kawaji, Hiromi Nagano, et al.
Molecular Imaging and Biology (2022) Vol. 25, Iss. 2, pp. 303-313
Closed Access | Times Cited: 11
Repeatability of radiomics studies in colorectal cancer: a systematic review
Ying Liu, Xiaoqin Wei, Feng Xu, et al.
BMC Gastroenterology (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 6
Radiomic Phenotypes for Improving Early Prediction of Survival in Stage III Non-Small Cell Lung Cancer Adenocarcinoma after Chemoradiation
José Marcio Luna, Andrew R. Barsky, Russell T. Shinohara, et al.
Cancers (2022) Vol. 14, Iss. 3, pp. 700-700
Open Access | Times Cited: 10
Clinical Significance of Peritumoral Adipose Tissue PET/CT Imaging Features for Predicting Axillary Lymph Node Metastasis in Patients with Breast Cancer
Jeong Won Lee, Sung Yong Kim, Sun Wook Han, et al.
Journal of Personalized Medicine (2021) Vol. 11, Iss. 10, pp. 1029-1029
Open Access | Times Cited: 13
The usefulness of machine-learning-based evaluation of clinical and pretreatment 18F-FDG-PET/CT radiomic features for predicting prognosis in patients with laryngeal cancer
Masatoyo Nakajo, Hiromi Nagano, Megumi Jinguji, et al.
British Journal of Radiology (2023) Vol. 96, Iss. 1149
Open Access | Times Cited: 5
A Machine Learning Approach Using FDG PET-Based Radiomics for Prediction of Tumor Mutational Burden and Prognosis in Stage IV Colorectal Cancer
Hyunjong Lee, Seung Hwan Moon, Jung Yong Hong, et al.
Cancers (2023) Vol. 15, Iss. 15, pp. 3841-3841
Open Access | Times Cited: 5
Radiomics in Oncological PET Imaging: A Systematic Review—Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers
David Morland, Elizabeth Katherine Anna Triumbari, Luca Boldrini, et al.
Diagnostics (2022) Vol. 12, Iss. 6, pp. 1330-1330
Open Access | Times Cited: 8
Prognostic and predictive value of radiomics features at MRI in nasopharyngeal carcinoma
Dan Bao, Yanfeng Zhao, Zhou Liu, et al.
Discover Oncology (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 8
Radiomics for predicting survival in patients with locally advanced rectal cancer: a systematic review and meta-analysis
Yaru Feng, Jing Gong, Tingdan Hu, et al.
Quantitative Imaging in Medicine and Surgery (2023) Vol. 13, Iss. 12, pp. 8395-8412
Open Access | Times Cited: 3
Evaluation of survival of the patients with metastatic rectal cancer by staging 18F-FDG PET/CT radiomic and volumetric parameters
Nurşin Agüloğlu, Ayşegül Aksu
Revista Española de Medicina Nuclear e Imagen Molecular (English Edition) (2022) Vol. 42, Iss. 2, pp. 122-128
Closed Access | Times Cited: 5
Primary tumor heterogeneity on pretreatment 18F-FDG PET/CT to predict outcome in patients with rectal cancer who underwent surgery after neoadjuvant therapy
Seda Gülbahar Ateş, Gülay Dilek, Gülin Uçmak
Revista Española de Medicina Nuclear e Imagen Molecular (English Edition) (2023) Vol. 42, Iss. 4, pp. 223-230
Closed Access | Times Cited: 2
The prognostic value of [18F]FDG PET/CT texture analysis prior to transplantation for unresectable colorectal liver metastases
Nadide Mutlukoca Stern, Lars Tore Gyland Mikalsen, Svein Dueland, et al.
Clinical Physiology and Functional Imaging (2024)
Open Access
Beads phantom for evaluating heterogeneity of SUV on 18F-FDG PET images
Koichi Okuda, Hisahiro Saito, Shozo Yamashita, et al.
Annals of Nuclear Medicine (2022) Vol. 36, Iss. 5, pp. 495-503
Closed Access | Times Cited: 2
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