Justin Ko

82 papers receiving 9.8k citations

Justin Ko's Hit Papers

Dermatologist-level classification of skin cancer with deep neural networks 2017 · 8.2k citations
8.2k0+3+6Years since publication2.5k5.0k7.5k

Peers

Justin Ko
Comparison fields: 5 of 207
  • Health Informatics 1.2k
  • Urology 708
  • Artificial Intelligence 3.3k
  • Radiology, Nuclear Medicine and Imaging 2.1k
  • Health Information Management 401
Replace Anil V. Parwani with:
Anil V. Parwani United States
Roberto A. Novoa United States
Liron Pantanowitz United States
Michael W. Kattan United States
Joann G. Elmore United States
Lawrence H. Schwartz United States
Susan M. Swetter United States
Andre Esteva United States
Jeroen van der Laak Netherlands
H. Peter Soyer Australia
Justin Ko relative to Anil V. Parwani United States Anil V. Parwani's profile →
Citations per field
00.5×4.2×
Anil V. Parwani · 1×
Citations per year

Countries citing papers authored by Justin Ko

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

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.

Border = papers with Justin Ko Line = papers co-authored together Justin Ko links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Dermatologist-level classification of skin cancer with deep neural networks
Hit paper breakdown →
20178222
2
Safety and efficacy of the JAK inhibitor tofacitinib citrate in patients with alopecia areata
Hit paper breakdown →
2016264
3 2008233
4 2020178
5 201091
6 202191
7 200689
8 202069
9 202061
10 202061
11 202049
12 202249
13 202044
14 202142
15 202239
16 202337
17 202028
18 202227
19 201925
20 201924

About Justin Ko

Justin Ko is a scholar working on Oncology, Dermatology, Urology, Public Health, Environmental and Occupational Health and Epidemiology, having authored 92 papers that have together received 10.2k indexed citations. Recurring topics across this work include Hair Growth and Disorders (25 papers), Cutaneous Melanoma Detection and Management (24 papers), Dermatology and Skin Diseases (15 papers), AI in cancer detection (8 papers), Dermatologic Treatments and Research (6 papers), Allergic Rhinitis and Sensitization (6 papers), Digital Imaging in Medicine (5 papers) and Autoimmune Bullous Skin Diseases (4 papers). The work is most often cited by research in Health Informatics (1.2k citations), Urology (708 citations), Artificial Intelligence (3.3k citations), Radiology, Nuclear Medicine and Imaging (2.1k citations) and Health Information Management (401 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, British Journal of Dermatology and Journal of Investigative Dermatology Symposium Proceedings.

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.

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