Justin Ko
Impact in
- Health Informatics top 0.01%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 0.2%
- AI in cancer detection
Papers in
- Urology 25
- Hair Growth and Disorders 25
- Dermatology 34
- Dermatology and Skin Diseases 17
- Dermatologic Treatments and Research 11
- Co-authors
- Roberto A. NovoaSusan M. SwetterAndre EstevaSebastian ThrunHelen M. BlauAlice B. GottliebBrett KingDavid E. Fisher
- Journals
- Journal of the American Academy of Dermatology (13 papers)Journal of Investigative Dermatology (8 papers)JAMA Dermatology (6 papers)Journal of Investigative Dermatology Symposium Proceedings (4 papers)British Journal of Dermatology (4 papers)
- Partner nations
- United StatesJapanUnited Kingdom
In The Last Decade
Justin Ko
78 papers receiving 9.4k citations
Hit Papers
Peers
Comparison fields: 5 of 208
- Health Informatics 1.3k
- Artificial Intelligence 3.7k
- Radiology, Nuclear Medicine and Imaging 2.6k
- Dermatology 951
- Urology 678
Countries citing papers authored by Justin Ko
This map shows the geographic impact of Justin Ko'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 Justin Ko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justin Ko more than expected).
Fields of papers citing papers by Justin Ko
This network shows the impact of papers produced by Justin Ko. 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 Justin Ko. The network helps show where Justin Ko may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Justin Ko, 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 | 1 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 14 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 5 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 9 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 27 | |
| 10 | 2023 | 0 | |
| 11 | 2022 | 6 | |
| 12 | 2022 | 4 | |
| 13 | 2022 | 25 | |
| 14 | 2020 | 67 | |
| 15 | 2020 | 4 | |
| 16 | 2020 | 27 | |
| 17 | 2020 | 57 | |
| 18 | 2020 | 41 | |
| 19 | 2020 | 5 | |
| 20 | 2019 | 25 |
About Justin Ko
Justin Ko is a scholar working on Urology, Dermatology, Health Informatics, Immunology and Allergy and Oncology, having authored 89 papers that have together received 9.8k indexed citations. Recurring topics across this work include Hair Growth and Disorders (25 papers), Cutaneous Melanoma Detection and Management (25 papers), Dermatology and Skin Diseases (17 papers), Dermatologic Treatments and Research (11 papers), AI in cancer detection (10 papers), Allergic Rhinitis and Sensitization (7 papers), Autoimmune Bullous Skin Diseases (7 papers) and Telemedicine and Telehealth Implementation (6 papers). The work is most often cited by research in Health Informatics (1.3k citations), Artificial Intelligence (3.7k citations), Radiology, Nuclear Medicine and Imaging (2.6k citations), Dermatology (951 citations) and Urology (678 citations). Justin Ko has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Roberto A. Novoa, Susan M. Swetter, Andre Esteva, Sebastian Thrun, Helen M. Blau, Alice B. Gottlieb, Brett King, David E. Fisher, Natasha Atanaskova Mesinkovska and Yves Dutronc. Their work appears in journals such as Journal of the American Academy of Dermatology, Journal of Investigative Dermatology, JAMA Dermatology, Journal of Investigative Dermatology Symposium Proceedings and British Journal of Dermatology.
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.