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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:

Stacking Ensemble Learning–Based [18F]FDG PET Radiomics for Outcome Prediction in Diffuse Large B-Cell Lymphoma
Shuilin Zhao, Jing Wang, Chentao Jin, et al.
Journal of Nuclear Medicine (2023) Vol. 64, Iss. 10, pp. 1603-1609
Open Access | Times Cited: 16

Showing 16 citing articles:

Comparing three-dimensional and two-dimensional deep-learning, radiomics, and fusion models for predicting occult lymph node metastasis in laryngeal squamous cell carcinoma based on CT imaging: a multicentre, retrospective, diagnostic study
Wenlun Wang, Hui Liang, Zhouyi Zhang, et al.
EClinicalMedicine (2024) Vol. 67, pp. 102385-102385
Open Access | Times Cited: 29
Radiomics-clinical nomogram for preoperative lymph node metastasis prediction in esophageal carcinoma
Xiaotao Geng, Yaping Zhang, Yang Li, et al.
British Journal of Radiology (2024) Vol. 97, Iss. 1155, pp. 652-659
Open Access | Times Cited: 7
Multi-omics-based prognostic prediction for locally advanced hypopharyngeal cancer treated with postoperative chemoradiotherapy: a dual-center study
Sixue Dong, Zian Yao, Zhiyuan Zhang, et al.
Research Square (Research Square) (2025)
Closed Access
The Evolution of Artificial Intelligence in Nuclear Medicine
Leonor Lopes, Alejandro López-Montes, Yizhou Chen, et al.
Seminars in Nuclear Medicine (2025)
Open Access
18F-FDG PET radiomics score construction by automatic machine learning for treatment response prediction in elderly patients with diffuse large B-cell lymphoma: a multicenter study
Jin-cheng Zhao, Wenzhuo Zhao, Man Chen, et al.
Journal of Cancer Research and Clinical Oncology (2025) Vol. 151, Iss. 3
Open Access
Comparing Habitat, Radiomics and Fusion Models for Predicting Micropapillary/Solid Components in Clinical Stage I Lung Adenocarcinoma: A Multicenter, Retrospective Study
Shaoyu Huang, Xin Liang, Lin Hua, et al.
(2025)
Closed Access
Prognosis Prediction of Diffuse Large B-Cell Lymphoma in $^{18}$F-FDG PET Images Based on Multi-Deep-Learning Models
Chunjun Qian, Chong Jiang, Kai Xie, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 7, pp. 4010-4023
Closed Access | Times Cited: 3
Baseline 18F-FDG PET/CT radiomics for prognosis prediction in diffuse large B cell lymphoma with extranodal involvement
Fenglian Jing, Xinchao Zhang, Yunuan Liu, et al.
Clinical & Translational Oncology (2024)
Closed Access | Times Cited: 3
Enhancing Lymphoma Diagnosis, Treatment, and Follow-Up Using 18F-FDG PET/CT Imaging: Contribution of Artificial Intelligence and Radiomics Analysis
Saeed Shafiee Hasanabadi, Seyed Mahmud Reza Aghamiri, Ahmad Ali Abin, et al.
Cancers (2024) Vol. 16, Iss. 20, pp. 3511-3511
Open Access | Times Cited: 3
Semiquantitative 2-[18F]FDG PET/CT-based parameters role in lymphoma
Domenico Albano, Marco Ravanelli, Rexhep Durmo, et al.
Frontiers in Medicine (2024) Vol. 11
Open Access | Times Cited: 3
Baseline 18F-FDG PET Radiomics Predicting Therapeutic Efficacy of Diffuse Large B-Cell Lymphoma after R-CHOP (-Like) Therapy
Fenglian Jing, Xinchao Zhang, Yunuan Liu, et al.
Cancer Biotherapy and Radiopharmaceuticals (2024)
Closed Access | Times Cited: 1
Stacking learning based on micro-CT radiomics for outcome prediction in the early-stage of silica-induced pulmonary fibrosis model
Hongwei Wang, Qiyue Jia, Yan Wang, et al.
Heliyon (2024) Vol. 10, Iss. 9, pp. e30651-e30651
Open Access
Multi-Omics-Based Prognostic Prediction for Locally Advanced Hypopharyngeal Cancer Treated with Surgery and Postoperative Chemoradiotherapy: A Dual-Center Study
Sixue Dong, Zian Yao, Zhiyuan Zhang, et al.
(2024)
Closed Access
Survival prediction in diffuse large B-cell lymphoma patients: multimodal PET/CT deep features radiomic model utilizing automated machine learning
Jianxin Chen, Fengyi Lin, Zhaoyan Dai, et al.
Journal of Cancer Research and Clinical Oncology (2024) Vol. 150, Iss. 10
Open Access
18F-FDG PET/CT-based habitat radiomics combining stacking ensemble learning for predicting prognosis in hepatocellular carcinoma: a multi-center study
Chunxiao Sui, Qian Su, Kun Chen, et al.
BMC Cancer (2024) Vol. 24, Iss. 1
Open Access
Clinical scoring systems, molecular subtypes and baseline [18F]FDG PET/CT image analysis for prognosis of diffuse large B-cell lymphoma
Zhenliang Sun, Tianshuo Yang, Chongyang Ding, et al.
Cancer Imaging (2024) Vol. 24, Iss. 1
Open Access
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