David Nam

577 citations
23 papers · 368 · 1 hit paper · h-index 7

Impact in

Papers in

David Nam

18 papers receiving 361 citations

David Nam's Hit Papers

Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction 2022 · 119 citations
1190+1+2Years since publication255075100

Peers

David Nam
Comparison fields: 5 of 74
  • Health Informatics 15
  • Immunology 143
  • Hepatology 52
  • Oncology 108
  • Health Information Management 18
Replace Mai Chan Lau with:
Mai Chan Lau Singapore
Rui Tang China
Aaron Maxwell United States
Christoph Grouls Germany
Saiaditya Badeti United States
Hong Ai China
Shufeng Xu China
Andrew Ju United States
Zhinan Xia China
David Nam relative to Mai Chan Lau Singapore Mai Chan Lau's profile →
Citations per field
00.5×10×15×18×
Mai Chan Lau · 1×
Citations per year

Countries citing papers authored by David Nam

Since Specialization
Citations

This map shows the geographic impact of David Nam'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 David Nam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Nam more than expected).

Fields of papers citing papers by David Nam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Nam. 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 David Nam. The network helps show where David Nam may publish in the future.

Co-authors

The 25 scholars most cited alongside David Nam, 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 David Nam Line = papers co-authored together David Nam links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020160
2
Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction
Hit paper breakdown →
2022119
3 202016
4 202214
5 202112
6 20167
7 20216
8 20245
9 20195
10 20235
11 20175
12 20103
13 20173
14 20223
15 20172
16 20241
17 20221
18 20141
19 20240
20 20190

About David Nam

David Nam is a scholar working on Electrical and Electronic Engineering, Oncology, Molecular Biology, Pulmonary and Respiratory Medicine and Immunology, having authored 23 papers that have together received 368 indexed citations. Recurring topics across this work include Silicon Carbide Semiconductor Technologies (9 papers), Multilevel Inverters and Converters (5 papers), Advanced DC-DC Converters (5 papers), Electromagnetic Compatibility and Noise Suppression (5 papers), Hepatocellular Carcinoma Treatment and Prognosis (3 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (2 papers), Genetic factors in colorectal cancer (2 papers) and Cancer Research and Treatments (2 papers). The work is most often cited by research in Health Informatics (15 citations), Immunology (143 citations), Hepatology (52 citations), Oncology (108 citations) and Health Information Management (18 citations). David Nam has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Valérie Paradis, Tobias Paul Seraphin, Julius Chapiro, Jakob Nikolas Kather, Adriana M. Mujal, Nina K. Serwas, Mikhail Binnewies, Megan K. Ruhland, Edward W. Roberts and Matthew F. Krummel. Their work appears in journals such as Journal of Clinical Oncology, JHEP Reports, Radiology, IEEE Transactions on Power Electronics and American Journal of Hematology.

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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