Junghwan Cho
Impact in
- Health Informatics top 10%
- Bioengineering top 10%
- Analytical Chemistry and Sensors
Papers in
-
- AI in cancer detection 9
-
- Advanced Chemical Sensor Technologies 5
- Biosensors and Analytical Detection 3
- Co-authors
- Paul J. Gemperline (2 shared papers)Se‐Hwan Paek (3 shared papers)Pradeep Kurup (6 shared papers)Sung-Min Seo (2 shared papers)Eunmi Lee (10 shared papers)Seungwan Kim (2 shared papers)Dwight S. Walker (1 shared paper)Jeong-Woo Son (3 shared papers)
- Journals
- Life (4 papers)Sensors and Actuators B Chemical (3 papers)Current Neurovascular Research (2 papers)Microchemical Journal (2 papers)Journal of Animal Science and Biotechnology (1 paper)
- Partner nations
- South KoreaUnited StatesJapan
In The Last Decade
Junghwan Cho
44 papers receiving 560 citations
Peers
Comparison fields: 5 of 105
- Health Informatics 11
- Bioengineering 41
- Neurology 55
- Neurology 93
- Biomedical Engineering 157
Countries citing papers authored by Junghwan Cho
This map shows the geographic impact of Junghwan Cho'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 Junghwan Cho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junghwan Cho more than expected).
Fields of papers citing papers by Junghwan Cho
This network shows the impact of papers produced by Junghwan Cho. 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 Junghwan Cho. The network helps show where Junghwan Cho may publish in the future.
Co-authors
The 25 scholars most cited alongside Junghwan Cho, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 102 | |
| 2 | 2016 | 52 | |
| 3 | 2016 | 44 | |
| 4 | 2011 | 39 | |
| 5 | 1995 | 35 | |
| 6 | 2003 | 34 | |
| 7 | 2020 | 33 | |
| 8 | 2014 | 29 | |
| 9 | 2021 | 22 | |
| 10 | 2023 | 18 | |
| 11 | 2022 | 16 | |
| 12 | 2012 | 15 | |
| 13 | Medical Image Deep Learning with Hospital PACS Dataset. | 2015 | 13 |
| 14 | 1995 | 13 | |
| 15 | 2002 | 13 | |
| 16 | 2023 | 10 | |
| 17 | 2011 | 9 | |
| 18 | 2022 | 8 | |
| 19 | 2021 | 7 | |
| 20 | 2021 | 7 |
About Junghwan Cho
Junghwan Cho is a scholar working on Artificial Intelligence, Biomedical Engineering, Molecular Biology, Oncology and Epidemiology, having authored 51 papers that have together received 585 indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), Advanced Chemical Sensor Technologies (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Cervical Cancer and HPV Research (3 papers), Biosensors and Analytical Detection (3 papers), Intracerebral and Subarachnoid Hemorrhage Research (3 papers), Endometrial and Cervical Cancer Treatments (3 papers) and Analytical Chemistry and Sensors (3 papers). The work is most often cited by research in Health Informatics (11 citations), Bioengineering (41 citations), Neurology (55 citations), Neurology (93 citations) and Biomedical Engineering (157 citations). Junghwan Cho has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Paul J. Gemperline, Se‐Hwan Paek, Pradeep Kurup, Sung-Min Seo, Eunmi Lee, Seungwan Kim, Dwight S. Walker, Jeong-Woo Son, Sin-Youl Park and Jayant Kumar. Their work appears in journals such as Life, Sensors and Actuators B Chemical, Current Neurovascular Research, Microchemical Journal and Journal of Animal Science and Biotechnology.
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.