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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:

Cancer Imaging Phenomics via CaPTk: Multi-Institutional Prediction of Progression-Free Survival and Pattern of Recurrence in Glioblastoma
Anahita Fathi Kazerooni, Hamed Akbari, Garima Shukla, et al.
JCO Clinical Cancer Informatics (2020), Iss. 4, pp. 234-244
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Federated learning enables big data for rare cancer boundary detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 170
The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics
Spyridon Bakas, Chiharu Sako, Hamed Akbari, et al.
Scientific Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 72
Clinical measures, radiomics, and genomics offer synergistic value in AI-based prediction of overall survival in patients with glioblastoma
Anahita Fathi Kazerooni, Sanjay Saxena, Erik Toorens, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 45
Applications of Radiomics and Radiogenomics in High-Grade Gliomas in the Era of Precision Medicine
Anahita Fathi Kazerooni, Stephen Bagley, Hamed Akbari, et al.
Cancers (2021) Vol. 13, Iss. 23, pp. 5921-5921
Open Access | Times Cited: 49
Radiomics and radiogenomics in pediatric neuro-oncology: A review
Rachel Madhogarhia, Debanjan Haldar, Sina Bagheri, et al.
Neuro-Oncology Advances (2022) Vol. 4, Iss. 1
Open Access | Times Cited: 28
GaNDLF: the generally nuanced deep learning framework for scalable end-to-end clinical workflows
Sarthak Pati, Siddhesh Thakur, İbrahim Ethem Hamamcı, et al.
Communications Engineering (2023) Vol. 2, Iss. 1
Open Access | Times Cited: 18
Workflow Applications of Artificial Intelligence in Radiology and an Overview of Available Tools
Neena Kapoor, Ronilda Lacson, Ramin Khorasani
Journal of the American College of Radiology (2020) Vol. 17, Iss. 11, pp. 1363-1370
Closed Access | Times Cited: 40
Reinventing radiation therapy with machine learning and imaging bio-markers (radiomics): State-of-the-art, challenges and perspectives
Laurent Dercle, Théophraste Henry, Alexandre Carré, et al.
Methods (2020) Vol. 188, pp. 44-60
Closed Access | Times Cited: 38
Analyzing magnetic resonance imaging data from glioma patients using deep learning
Bjoern Menze, Fabian Isensee, Roland Wiest, et al.
Computerized Medical Imaging and Graphics (2020) Vol. 88, pp. 101828-101828
Open Access | Times Cited: 36
Reproducibility analysis of multi‐institutional paired expert annotations and radiomic features of the Ivy Glioblastoma Atlas Project (Ivy GAP) dataset
Sarthak Pati, Ruchika Verma, Hamed Akbari, et al.
Medical Physics (2020) Vol. 47, Iss. 12, pp. 6039-6052
Open Access | Times Cited: 30
Artificial intelligence in tumor subregion analysis based on medical imaging: A review
Mingquan Lin, Jacob Wynne, Boran Zhou, et al.
Journal of Applied Clinical Medical Physics (2021) Vol. 22, Iss. 7, pp. 10-26
Open Access | Times Cited: 25
Artificial Intelligence for Survival Prediction in Brain Tumors on Neuroimaging
Anne Jian, Sidong Liu, Antonio Di Ieva
Neurosurgery (2022) Vol. 91, Iss. 1, pp. 8-26
Closed Access | Times Cited: 15
Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements
Javier Villanueva-Meyer, Spyridon Bakas, Pallavi Tiwari, et al.
The Lancet Oncology (2024) Vol. 25, Iss. 11, pp. e581-e588
Closed Access | Times Cited: 2
Predicting Short-Term Survival after Gross Total or Near Total Resection in Glioblastomas by Machine Learning-Based Radiomic Analysis of Preoperative MRI
Santiago Cepeda, Ángel Pérez‐Núñez, Sergio García-García, et al.
Cancers (2021) Vol. 13, Iss. 20, pp. 5047-5047
Open Access | Times Cited: 18
Quantification of tumor microenvironment acidity in glioblastoma using principal component analysis of dynamic susceptibility contrast enhanced MR imaging
Hamed Akbari, Anahita Fathi Kazerooni, Jeffrey B. Ware, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 16
Expert tumor annotations and radiomics for locally advanced breast cancer in DCE-MRI for ACRIN 6657/I-SPY1
Rhea Chitalia, Sarthak Pati, Megh Bhalerao, et al.
Scientific Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 11
Visualizing Glioma Infiltration by the Combination of Multimodality Imaging and Artificial Intelligence, a Systematic Review of the Literature
Sabrina Honoré d’Este, Michael Bachmann Nielsen, Adam E. Hansen
Diagnostics (2021) Vol. 11, Iss. 4, pp. 592-592
Open Access | Times Cited: 14
Radiogenomic Predictors of Recurrence in Glioblastoma—A Systematic Review
Felix Corr, Dustin Grimm, Benjamin Saß, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 3, pp. 402-402
Open Access | Times Cited: 10
Enhancing the REMBRANDT MRI collection with expert segmentation labels and quantitative radiomic features
Anousheh Sayah, Camelia Bencheqroun, Krithika Bhuvaneshwar, et al.
Scientific Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 10
Identification of phenomic data in the pathogenesis of cancers of the gastrointestinal (GI) tract in the UK biobank
Shirin Hui Tan, Catherina Anak Guan, Mohamad Adam Bujang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Radiomic and Volumetric Measurements as Clinical Trial Endpoints—A Comprehensive Review
Ionut-Gabriel Funingana, Pubudu Piyatissa, Marika Reinius, et al.
Cancers (2022) Vol. 14, Iss. 20, pp. 5076-5076
Open Access | Times Cited: 7
Pretreatment MR-based radiomics in patients with glioblastoma: A systematic review and meta-analysis of prognostic endpoints
Yangsean Choi, Jinhee Jang, Bum‐Soo Kim, et al.
European Journal of Radiology (2023) Vol. 168, pp. 111130-111130
Open Access | Times Cited: 3
Optimization of Deep Learning Based Brain Extraction in MRI for Low Resource Environments
Siddhesh Thakur, Sarthak Pati, Ravi Panchumarthy, et al.
Lecture notes in computer science (2022), pp. 151-167
Open Access | Times Cited: 5
A Neural Network Approach to Identify Glioblastoma Progression Phenotype from Multimodal MRI
Jiun‐Lin Yan, Cheng‐Hong Toh, L. V. Ko, et al.
Cancers (2021) Vol. 13, Iss. 9, pp. 2006-2006
Open Access | Times Cited: 7
The power of integrating multiple data sources in medical imaging: A study of MGMT methylation status
Mariya Miteva, Maria Nisheva-Pavlova
Procedia Computer Science (2024) Vol. 239, pp. 1196-1203
Open Access
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