Saeed Hassanpour
- Health Informatics top 0.2%
- Artificial Intelligence in Healthcare and Education 6
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- Radiomics and Machine Learning in Medical Imaging 16
- Artificial Intelligence top 1%
- AI in cancer detection 20
- Topic Modeling 11
- Natural Language Processing Techniques 8
- Oncology top 5%
- Colorectal Cancer Screening and Detection 14
- Applied Psychology top 10%
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- Biomedical Text Mining and Ontologies 12
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- Substance Abuse Treatment and Outcomes 6
- Co-authors
- Naofumi TomitaCurtis P. LanglotzManu GoyalYvonne Y. CheungArief A. SuriawinataShaofeng YanThomas KnackstedtMatthew A. Suriawinata
- Journals
- Circulation (1 paper)SHILAP Revista de lepidopterología (1 paper)Oncogene (1 paper)
- Partner nations
- United StatesUnited KingdomNetherlands
In The Last Decade
Saeed Hassanpour
72 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Health Informatics 305
- Radiology, Nuclear Medicine and Imaging 751
- Artificial Intelligence 926
- Oncology 576
- Applied Psychology 78
Countries citing papers authored by Saeed Hassanpour
This map shows the geographic impact of Saeed Hassanpour'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 Saeed Hassanpour with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saeed Hassanpour more than expected).
Fields of papers citing papers by Saeed Hassanpour
This network shows the impact of papers produced by Saeed Hassanpour. 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 Saeed Hassanpour. The network helps show where Saeed Hassanpour may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Saeed Hassanpour, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 7 | |
| 5 | 2024 | 11 | |
| 6 | 2024 | 1 | |
| 7 | 2023 | 0 | |
| 8 | 2022 | 4 | |
| 9 | 2022 | 79 | |
| 10 | 2022 | 1 | |
| 11 | 2022 | 10 | |
| 12 | 2021 | 7 | |
| 13 | 2021 | 8 | |
| 14 | 2020 | 8 | |
| 15 | 2019 | 6 | |
| 16 | 2019 | 15 | |
| 17 | 2019 | 2 | |
| 18 | 2019 | 57 | |
| 19 | Finding a Needle in the Haystack: Attention-Based Classification of High Resolution Microscopy Images. | 2018 | 4 |
| 20 | A Rule Management and Elicitation Tool for SWRL Rule Bases. | 2009 | 1 |
About Saeed Hassanpour
Saeed Hassanpour is a scholar working on Health Informatics, Issues, ethics and legal aspects and Artificial Intelligence, having authored 80 papers that have together received 2.1k indexed citations. Recurring topics across this work include AI in cancer detection (20 papers), Radiomics and Machine Learning in Medical Imaging (16 papers), Colorectal Cancer Screening and Detection (14 papers), Biomedical Text Mining and Ontologies (12 papers), Topic Modeling (11 papers), Natural Language Processing Techniques (8 papers), Substance Abuse Treatment and Outcomes (6 papers) and Artificial Intelligence in Healthcare and Education (6 papers). The work is most often cited by research in Health Informatics (305 citations), Radiology, Nuclear Medicine and Imaging (751 citations) and Artificial Intelligence (926 citations). Saeed Hassanpour has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Naofumi Tomita, Curtis P. Langlotz, Manu Goyal, Yvonne Y. Cheung, Arief A. Suriawinata, Shaofeng Yan, Thomas Knackstedt, Matthew A. Suriawinata, Lorenzo Torresani and Lisa A. Marsch. Their work appears in journals such as Circulation, SHILAP Revista de lepidopterología and Oncogene.
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.