Richard Ha
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
-
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 28
- MRI in cancer diagnosis 18
- Co-authors
- Simukayi MutasaDipanjan BanerjeeVictoria L. MangoRalph WynnMichael Z. LiuShawn SunSachin JambawalikarGuson Kang
- Journals
- American Journal of Roentgenology (8 papers)Clinical Breast Cancer (6 papers)Academic Radiology (6 papers)Journal of Digital Imaging (5 papers)Journal of Magnetic Resonance Imaging (5 papers)
- Partner nations
- United StatesFranceAustralia
In The Last Decade
Richard Ha
95 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 148
- Health Informatics 155
- Radiology, Nuclear Medicine and Imaging 1.0k
- Cancer Research 504
- Virology 136
- Pathology and Forensic Medicine 390
Countries citing papers authored by Richard Ha
This map shows the geographic impact of Richard Ha'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 Richard Ha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard Ha more than expected).
Fields of papers citing papers by Richard Ha
This network shows the impact of papers produced by Richard Ha. 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 Richard Ha. The network helps show where Richard Ha may publish in the future.
Co-authors
The 25 scholars most cited alongside Richard Ha, 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 | 16 | |
| 3 | 2023 | 9 | |
| 4 | 2019 | 11 | |
| 5 | 2019 | 31 | |
| 6 | 2018 | 45 | |
| 7 | 2018 | 26 | |
| 8 | 2018 | 38 | |
| 9 | 2018 | 1 | |
| 10 | 2018 | 4 | |
| 11 | 2018 | 21 | |
| 12 | 2017 | 42 | |
| 13 | 2017 | 26 | |
| 14 | 2017 | 4 | |
| 15 | 2016 | 9 | |
| 16 | 2016 | 0 | |
| 17 | 2014 | 11 | |
| 18 | 2009 | 2 | |
| 19 | 2003 | 27 | |
| 20 | 2001 | 22 |
About Richard Ha
Richard Ha is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging, Cancer Research, Pathology and Forensic Medicine and Artificial Intelligence, having authored 101 papers that have together received 2.6k indexed citations. Recurring topics across this work include AI in cancer detection (29 papers), Radiomics and Machine Learning in Medical Imaging (28 papers), Breast Cancer Treatment Studies (27 papers), Breast Lesions and Carcinomas (20 papers), MRI in cancer diagnosis (18 papers), Digital Radiography and Breast Imaging (16 papers), Mechanical Circulatory Support Devices (15 papers) and Cardiac Structural Anomalies and Repair (10 papers). The work is most often cited by research in Health Informatics (155 citations), Radiology, Nuclear Medicine and Imaging (1.0k citations), Cancer Research (504 citations), Virology (136 citations) and Pathology and Forensic Medicine (390 citations). Richard Ha has collaborated with scholars based in United States, France and Australia. Frequent co-authors include Simukayi Mutasa, Dipanjan Banerjee, Victoria L. Mango, Ralph Wynn, Michael Z. Liu, Shawn Sun, Sachin Jambawalikar, Guson Kang, Peter Chang and Jenika Karcich. Their work appears in journals such as American Journal of Roentgenology, Clinical Breast Cancer, Academic Radiology, Journal of Digital Imaging and Journal of Magnetic Resonance Imaging.
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.