Masoumeh Gity
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- MRI in cancer diagnosis 17
- Radiomics and Machine Learning in Medical Imaging 15
- COVID-19 diagnosis using AI 10
- Health Informatics top 10%
- Obstetrics and Gynecology top 10%
- Reproductive Medicine top 10%
- Ovarian cancer diagnosis and treatment 6
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- Breast Lesions and Carcinomas 9
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- AI in cancer detection 8
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- COVID-19 Clinical Research Studies 5
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- COVID-19 and healthcare impacts 5
- Co-authors
- Hamid Soltanian‐ZadehMadjid ShakibaHamid Abrishami MoghaddamBehnaz MoradiMahrooz MalekC. LucasJing Yong YeSarah Taghavi Namin
- Journals
- Nature Communications (1 paper)SHILAP Revista de lepidopterología (8 papers)PLoS ONE (2 papers)
- Partner nations
- IranUnited StatesUnited Kingdom
In The Last Decade
Masoumeh Gity
61 papers receiving 497 citations
Peers
Comparison fields: 5 of 80
- Radiology, Nuclear Medicine and Imaging 279
- Health Informatics 14
- Obstetrics and Gynecology 44
- Reproductive Medicine 44
- Computer Vision and Pattern Recognition 91
Countries citing papers authored by Masoumeh Gity
This map shows the geographic impact of Masoumeh Gity'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 Masoumeh Gity with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masoumeh Gity more than expected).
Fields of papers citing papers by Masoumeh Gity
This network shows the impact of papers produced by Masoumeh Gity. 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 Masoumeh Gity. The network helps show where Masoumeh Gity may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Masoumeh Gity, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 0 | |
| 4 | 2023 | 34 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 1 | |
| 7 | 2021 | 2 | |
| 8 | 2020 | 13 | |
| 9 | 2020 | 1 | |
| 10 | 2020 | 14 | |
| 11 | 2019 | 0 | |
| 12 | 2019 | 12 | |
| 13 | 2019 | 13 | |
| 14 | Effect of Reconstruction Filters on Ultrasound Computed Tomography Image Quality in Two Different Detector Arrangements: A Preliminary Simulation Study | 2018 | 1 |
| 15 | 2017 | 6 | |
| 16 | 2017 | 32 | |
| 17 | 2016 | 6 | |
| 18 | Discrimination of Benign and Malignant Suspicious Breast Tumors Based on Semi-Quantitative DCE-MRI Parameters Employing Support Vector Machine | 2015 | 3 |
| 19 | 2014 | 7 | |
| 20 | Comparison of logistic regression and neural network models in predicting the outcome of biopsy in breast cancer from MRI findings | 2004 | 5 |
About Masoumeh Gity
Masoumeh Gity is a scholar working on Radiology, Nuclear Medicine and Imaging, Obstetrics and Gynecology and Reproductive Medicine, having authored 67 papers that have together received 511 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (17 papers), Radiomics and Machine Learning in Medical Imaging (15 papers), COVID-19 diagnosis using AI (10 papers), Breast Lesions and Carcinomas (9 papers), AI in cancer detection (8 papers), Ovarian cancer diagnosis and treatment (6 papers), COVID-19 Clinical Research Studies (5 papers) and COVID-19 and healthcare impacts (5 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (279 citations), Health Informatics (14 citations) and Obstetrics and Gynecology (44 citations). Masoumeh Gity has collaborated with scholars based in Iran, United States and United Kingdom. Frequent co-authors include Hamid Soltanian‐Zadeh, Madjid Shakiba, Hamid Abrishami Moghaddam, Behnaz Moradi, Mahrooz Malek, C. Lucas, Jing Yong Ye, Sarah Taghavi Namin, Hamidreza Saligheh Rad and Anahita Fathi Kazerooni. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.
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.