Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

An artificial intelligence method using FDG PET to predict treatment outcome in diffuse large B cell lymphoma patients
Maria C. Ferrández, Sandeep S.V. Golla, Jakoba J. Eertink, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 17

Showing 17 citing articles:

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: 4
A Scoping Review of Artificial Intelligence Applications in Clinical Trial Risk Assessment
Douglas Teodoro, Nona Naderi, Anthony Yazdani, et al.
medRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
The Use of Maximum-Intensity Projections and Deep Learning Adds Value to the Fully Automatic Segmentation of Lesions Avid for [18F]FDG and [68Ga]Ga-PSMA in PET/CT
Cláudia S. Constantino, Francisco P. M. Oliveira, Marisa Machado, et al.
Journal of Nuclear Medicine (2025), pp. jnumed.124.269067-jnumed.124.269067
Closed Access
Prognostic impact of metabolic tumor volume using the SUV4.0 segmentation threshold in 1,960 lymphoma patients from prospective LYSA trials
Solène Malmon, Mad‐Hélénie Elsensohn, Catherine Thieblemont, et al.
European Journal of Nuclear Medicine and Molecular Imaging (2025)
Closed Access
Development and validation of pan-cancer lesion segmentation AI-model for whole-body 18F-FDG PET/CT in diverse clinical cohorts
Fahmida Haque, Alex Chen, Nathan Lay, et al.
Computers in Biology and Medicine (2025) Vol. 190, pp. 110052-110052
Closed 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
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
Segmentation-Free Outcome Prediction from Head and Neck Cancer PET/CT Images: Deep Learning-Based Feature Extraction from Multi-Angle Maximum Intensity Projections (MA-MIPs)
Amirhosein Toosi, Isaac Shiri, Habib Zaidi, et al.
Cancers (2024) Vol. 16, Iss. 14, pp. 2538-2538
Open Access | Times Cited: 2
Validation of an Artificial Intelligence–Based Prediction Model Using 5 External PET/CT Datasets of Diffuse Large B-Cell Lymphoma
Maria C. Ferrández, Sandeep S.V. Golla, Jakoba J. Eertink, et al.
Journal of Nuclear Medicine (2024) Vol. 65, Iss. 11, pp. 1802-1807
Closed Access | Times Cited: 2
A robust deep-learning model for fully automatic segmentation of lymphoma lesions on whole-body [18F]FDG PET/CT images
Cláudia S. Constantino, Francisco P. M. Oliveira, Sónia Leocádio, et al.
(2024), pp. 1-4
Closed Access | Times Cited: 1
Artificial Intelligence Applications in Lymphoma Diagnosis and Management: Opportunities, Challenges, and Future Directions
Miao Shen, Zhinong Jiang
Journal of Multidisciplinary Healthcare (2024) Vol. Volume 17, pp. 5329-5339
Open Access | Times Cited: 1
Artificial Intelligence-Driven Precision Medicine: Multi-Omics and Spatial Multi-Omics Approaches in Diffuse Large B-Cell Lymphoma (DLBCL)
Yanping Shao, X.-Y. Lv, Shilong Ying, et al.
Frontiers in Bioscience-Landmark (2024) Vol. 29, Iss. 12
Open Access | Times Cited: 1
The Role of Artificial Intelligence and Machine Learning Methodologies in Bioinformatics
Dipthi Shree, B.L. Shiva Kumar, Vithiya Ganesan, et al.
(2024), pp. 194-201
Closed Access
Prediction of Total Metabolic Tumor Volume from Tissue-Wise FDG-PET/CT Projections, Interpreted Using Cohort Saliency Analysis
Sambit Tarai, Elin Lundström, Johan Öfverstedt, et al.
Lecture notes in computer science (2024), pp. 242-255
Closed Access
Imaging Tumor Metabolism and Its Heterogeneity: Special Focus on Radiomics and AI
László Papp, David Haberl, Boglarka Ecsedi, et al.
Interdisciplinary cancer research (2024)
Closed Access
A Systematic Review of the Applications of Deep Learning for the Interpretation of Positron Emission Tomography Images of Patients with Lymphoma
Theofilos Kanavos, Effrosyni Birbas, Theodoros P. Zanos
Cancers (2024) Vol. 17, Iss. 1, pp. 69-69
Open Access
Exploring the applicability of a lesion segmentation method on [18F]fluorothymidine PET/CT images in diffuse large B-cell lymphoma
G. Pitarch, Yamila Rotstein Habarnau, Roxana Chirico, et al.
European Journal of Hybrid Imaging (2023) Vol. 7, Iss. 1
Open Access
Page 1

Scroll to top