Mana Moassefi

588 total citations
24 papers, 372 citations indexed

About

Mana Moassefi is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Biomedical Engineering. According to data from OpenAlex, Mana Moassefi has authored 24 papers receiving a total of 372 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Health Informatics and 8 papers in Biomedical Engineering. Recurrent topics in Mana Moassefi's work include Radiomics and Machine Learning in Medical Imaging (15 papers), Artificial Intelligence in Healthcare and Education (8 papers) and Advanced X-ray and CT Imaging (5 papers). Mana Moassefi is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (15 papers), Artificial Intelligence in Healthcare and Education (8 papers) and Advanced X-ray and CT Imaging (5 papers). Mana Moassefi collaborates with scholars based in United States, Iran and Canada. Mana Moassefi's co-authors include Bradley J. Erickson, Shahriar Faghani, Bardia Khosravi, Pouria Rouzrokh, Yashbir Singh, Gian Marco Conte, Diana V. Vera-Garcia, Seyed Moein Rassoulinejad-Mousavi, Fred Nugen and Jaidip Jagtap and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and Gastrointestinal Endoscopy.

In The Last Decade

Mana Moassefi

21 papers receiving 367 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mana Moassefi United States 9 219 137 94 88 52 24 372
Sungwon Ham South Korea 9 202 0.9× 40 0.3× 63 0.7× 69 0.8× 24 0.5× 18 385
Khashayar Namdar Canada 10 280 1.3× 37 0.3× 71 0.8× 81 0.9× 64 1.2× 26 470
Tugba Akinci D’Antonoli Switzerland 13 449 2.1× 182 1.3× 153 1.6× 99 1.1× 54 1.0× 37 604
Rachel McCarroll United States 10 339 1.5× 35 0.3× 101 1.1× 62 0.7× 47 0.9× 19 475
Yinhui Deng China 10 174 0.8× 28 0.2× 75 0.8× 44 0.5× 57 1.1× 19 457
Jordan Wong Canada 8 204 0.9× 26 0.2× 77 0.8× 47 0.5× 46 0.9× 19 339
Christian V. Guthier United States 9 282 1.3× 83 0.6× 71 0.8× 61 0.7× 19 0.4× 27 416
G. Guidi Italy 13 236 1.1× 49 0.4× 63 0.7× 51 0.6× 13 0.3× 35 388
Weidao Chen China 11 153 0.7× 20 0.1× 72 0.8× 39 0.4× 29 0.6× 25 254
Camilla Scapicchio Italy 5 254 1.2× 28 0.2× 85 0.9× 68 0.8× 41 0.8× 9 336

Countries citing papers authored by Mana Moassefi

Since Specialization
Citations

This map shows the geographic impact of Mana Moassefi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mana Moassefi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mana Moassefi more than expected).

Fields of papers citing papers by Mana Moassefi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mana Moassefi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mana Moassefi. The network helps show where Mana Moassefi may publish in the future.

Co-authorship network of co-authors of Mana Moassefi

This figure shows the co-authorship network connecting the top 25 collaborators of Mana Moassefi. A scholar is included among the top collaborators of Mana Moassefi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mana Moassefi. Mana Moassefi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Khosravi, Bardia, et al.. (2025). A Current Review of Generative AI in Medicine: Core Concepts, Applications, and Current Limitations. Current Reviews in Musculoskeletal Medicine. 18(7). 246–266. 3 indexed citations
2.
Moassefi, Mana, Shahriar Faghani, Gian Marco Conte, et al.. (2024). Exploring the Impact of 3D Fast Spin Echo and Inversion Recovery Gradient Echo Sequences Magnetic Resonance Imaging Acquisition on Automated Brain Tumor Segmentation. SHILAP Revista de lepidopterología. 2(2). 231–240.
3.
Maleki, Farhad, Linda Moy, Reza Forghani, et al.. (2024). RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models. Journal of Imaging Informatics in Medicine. 38(4). 2524–2536. 2 indexed citations
4.
Khosravi, Bardia, Elham Mahmoudi, Pouria Rouzrokh, et al.. (2024). A Guideline for Open-Source Tools to Make Medical Imaging Data Ready for Artificial Intelligence Applications: A Society of Imaging Informatics in Medicine (SIIM) Survey. Journal of Imaging Informatics in Medicine. 37(5). 2015–2024.
5.
Moassefi, Mana, Shahriar Faghani, & Bradley J. Erickson. (2024). Artificial Intelligence in Neuro-Oncology: predicting molecular markers and response to therapy.. Medical Research Archives. 12(6). 1 indexed citations
6.
Moassefi, Mana, Yashbir Singh, Gian Marco Conte, et al.. (2024). Checklist for Reproducibility of Deep Learning in Medical Imaging. Journal of Imaging Informatics in Medicine. 37(4). 1664–1673. 6 indexed citations
7.
Moassefi, Mana, et al.. (2024). Empowering Women in Imaging Informatics: Confronting Imposter Syndrome, Addressing Microaggressions, and Striving for Work-Life Harmony. Journal of Imaging Informatics in Medicine. 38(3). 1291–1296.
8.
Conte, Gian Marco, Mana Moassefi, Shahriar Faghani, et al.. (2023). NIMG-57. PERFORMANCE OF DEEP LEARNING IN MGMT PROMOTER METHYLATION STATUS PREDICTION USING BRAIN MRI: RESULTS FROM A LARGE COHORT OF IDH-WILDTYPE GLIOMAS TESTED BY A SINGLE METHYLATION ASSAY. Neuro-Oncology. 25(Supplement_5). v199–v199. 1 indexed citations
9.
Rouzrokh, Pouria, Bardia Khosravi, Shahriar Faghani, et al.. (2023). THA-AID: Deep Learning Tool for Total Hip Arthroplasty Automatic Implant Detection With Uncertainty and Outlier Quantification. The Journal of Arthroplasty. 39(4). 966–973.e17. 17 indexed citations
10.
Faghani, Shahriar, Bardia Khosravi, Mana Moassefi, Gian Marco Conte, & Bradley J. Erickson. (2023). A Comparison of Three Different Deep Learning-Based Models to Predict the MGMT Promoter Methylation Status in Glioblastoma Using Brain MRI. Journal of Digital Imaging. 36(3). 837–846. 25 indexed citations
11.
Moassefi, Mana, Shahriar Faghani, Bardia Khosravi, Pouria Rouzrokh, & Bradley J. Erickson. (2023). Artificial Intelligence in Radiology: Overview of Application Types, Design, and Challenges. Seminars in Roentgenology. 58(2). 170–177. 6 indexed citations
12.
Moassefi, Mana, Pouria Rouzrokh, Gian Marco Conte, et al.. (2023). Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review. Journal of Digital Imaging. 36(5). 2306–2312. 11 indexed citations
13.
Faghani, Shahriar, Don C. Codipilly, Mana Moassefi, Prasad G. Iyer, & Bradley J. Erickson. (2023). Optimizing Storage and Computational Efficiency: An Efficient Algorithm for Whole Slide Image Size Reduction. SHILAP Revista de lepidopterología. 1(3). 419–424. 2 indexed citations
14.
Rouzrokh, Pouria, Bardia Khosravi, Shahriar Faghani, et al.. (2022). Mitigating Bias in Radiology Machine Learning: 1. Data Handling. Radiology Artificial Intelligence. 4(5). e210290–e210290. 81 indexed citations
15.
Faghani, Shahriar, Bardia Khosravi, Mana Moassefi, et al.. (2022). Mitigating Bias in Radiology Machine Learning: 3. Performance Metrics. Radiology Artificial Intelligence. 4(5). e220061–e220061. 63 indexed citations
16.
Khosravi, Bardia, Shahriar Faghani, Fred Nugen, et al.. (2022). Mitigating Bias in Radiology Machine Learning: 2. Model Development. Radiology Artificial Intelligence. 4(5). e220010–e220010. 59 indexed citations
17.
Khosravi, Bardia, Pouria Rouzrokh, Shahriar Faghani, et al.. (2022). Machine Learning and Deep Learning in Cardiothoracic Imaging: A Scoping Review. Diagnostics. 12(10). 2512–2512. 2 indexed citations
18.
Rouzrokh, Pouria, Bardia Khosravi, Mana Moassefi, et al.. (2022). Machine Learning in Cardiovascular Imaging: A Scoping Review of Published Literature. Current Radiology Reports. 11(2). 34–45. 6 indexed citations
19.
Moassefi, Mana, Shahriar Faghani, Gian Marco Conte, et al.. (2022). A deep learning model for discriminating true progression from pseudoprogression in glioblastoma patients. Journal of Neuro-Oncology. 159(2). 447–455. 27 indexed citations
20.
Faghani, Shahriar, Narges Karimi, Mana Moassefi, et al.. (2022). Validation of myasthenia gravis activity of daily living questionnaire: Persian version. PubMed. 21(1). 35–39. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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