Simon Han
Impact in
- Health Informatics top 10%
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 5
- COVID-19 diagnosis using AI 2
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- Lung Cancer Diagnosis and Treatment 3
- Co-authors
- Alex Bui (7 shared papers)Denise R. Aberle (4 shared papers)William Hsu (9 shared papers)Shiwen Shen (4 shared papers)Xuan Liu (1 shared paper)M A Baluda (1 shared paper)No-Hee Park (1 shared paper)Marisa C. Eisenberg (1 shared paper)
- Journals
- Journal of Vascular and Interventional Radiology (2 papers)Artificial Intelligence in Medicine (1 paper)Frontiers in Plant Science (1 paper)Expert Systems with Applications (1 paper)Frontiers in Neurology (1 paper)
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
Simon Han
16 papers receiving 345 citations
Peers
Comparison fields: 5 of 79
- Health Informatics 16
- Radiology, Nuclear Medicine and Imaging 170
- Pulmonary and Respiratory Medicine 146
- Health Information Management 20
- Artificial Intelligence 115
Countries citing papers authored by Simon Han
This map shows the geographic impact of Simon Han'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 Simon Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Han more than expected).
Fields of papers citing papers by Simon Han
This network shows the impact of papers produced by Simon Han. 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 Simon Han. The network helps show where Simon Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Simon Han, 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 | 2019 | 184 | |
| 2 | 1997 | 41 | |
| 3 | 2016 | 41 | |
| 4 | 2016 | 14 | |
| 5 | 2015 | 13 | |
| 6 | 2015 | 12 | |
| 7 | 2016 | 10 | |
| 8 | 2016 | 10 | |
| 9 | 2020 | 9 | |
| 10 | 2006 | 5 | |
| 11 | 2019 | 4 | |
| 12 | Explainable Hierarchical Semantic Convolutional Neural Network for Lung Cancer Diagnosis | 2019 | 3 |
| 13 | 2008 | 2 | |
| 14 | A Continuous Markov Model Approach Using Individual Patient Data to Estimate Mean Sojourn Time of Lung Cancer. | 2015 | 1 |
| 15 | 2024 | 1 | |
| 16 | 2018 | 1 | |
| 17 | 2025 | 0 | |
| 18 | 2025 | 0 | |
| 19 | 2025 | 0 |
About Simon Han
Simon Han is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Surgery, Molecular Biology and Oncology, having authored 19 papers that have together received 351 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), Lung Cancer Diagnosis and Treatment (3 papers), COVID-19 diagnosis using AI (2 papers), AI in cancer detection (2 papers), Growth Hormone and Insulin-like Growth Factors (2 papers), Global Cancer Incidence and Screening (2 papers), Thyroid Disorders and Treatments (1 paper) and Transcranial Magnetic Stimulation Studies (1 paper). The work is most often cited by research in Health Informatics (16 citations), Radiology, Nuclear Medicine and Imaging (170 citations), Pulmonary and Respiratory Medicine (146 citations), Health Information Management (20 citations) and Artificial Intelligence (115 citations). Simon Han has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Alex Bui, Denise R. Aberle, William Hsu, Shiwen Shen, Xuan Liu, M A Baluda, No-Hee Park, Marisa C. Eisenberg, Joseph J. DiStefano and P. Reed Larsen. Their work appears in journals such as Journal of Vascular and Interventional Radiology, Artificial Intelligence in Medicine, Frontiers in Plant Science, Expert Systems with Applications and Frontiers in Neurology.
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.