Daniel W. Kim

569 citations
27 papers · 324 · h-index 11

Impact in

  • Neurology top 10%
    • Neurofibromatosis and Schwannoma Cases
    • Glioma Diagnosis and Treatment

Papers in

    • Cancer Diagnosis and Treatment 3
    • Inflammatory Biomarkers in Disease Prognosis 2
    • Colorectal and Anal Carcinomas 3

Daniel W. Kim

23 papers receiving 318 citations

Peers

Daniel W. Kim
Comparison fields: 5 of 58
  • Neurology 94
  • Genetics 61
  • Otorhinolaryngology 24
  • Epidemiology 156
  • Endocrinology, Diabetes and Metabolism 46
Replace Micaela Motta with:
Micaela Motta Italy
Ed M. Noordijk Netherlands
Shari Rudoler United States
Raj Singh United States
Edward Yu Canada
Vijay Patil India
Cristina Veres France
Chiraz El‐Fayech France
Hannah Carolan Canada
A. Urgesi Italy
Daniel W. Kim relative to Micaela Motta Italy Micaela Motta's profile →
Citations per field
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Micaela Motta · 1×
Citations per year

Countries citing papers authored by Daniel W. Kim

Since Specialization
Citations

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

Fields of papers citing papers by Daniel W. Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel W. Kim. 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 Daniel W. Kim. The network helps show where Daniel W. Kim may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015101
2 202031
3 202031
4 201920
5 202117
6 202116
7 202116
8 201914
9 202014
10 202110
11 201210
12 20209
13 20196
14 20216
15 20195
16 20215
17 20193
18 20213
19 20202
20 20222

About Daniel W. Kim

Daniel W. Kim is a scholar working on Oncology, Surgery, Pulmonary and Respiratory Medicine, Epidemiology and Neurology, having authored 27 papers that have together received 324 indexed citations. Recurring topics across this work include Meningioma and schwannoma management (4 papers), Economic and Financial Impacts of Cancer (3 papers), Prostate Cancer Treatment and Research (3 papers), Prostate Cancer Diagnosis and Treatment (3 papers), Colorectal and Anal Carcinomas (3 papers), Neurofibromatosis and Schwannoma Cases (3 papers), Cancer Diagnosis and Treatment (3 papers) and Inflammatory Biomarkers in Disease Prognosis (2 papers). The work is most often cited by research in Neurology (94 citations), Genetics (61 citations), Otorhinolaryngology (24 citations), Epidemiology (156 citations) and Endocrinology, Diabetes and Metabolism (46 citations). Daniel W. Kim has collaborated with scholars based in United States, Germany and Netherlands. Frequent co-authors include William L. Hwang, Andrzej Niemierko, Helen A. Shih, Robert L. Martuza, William T. Curry, Fred G. Barker, Jay S. Loeffler, Kevin Oh, Ariel E. Marciscano and Grace Lee. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Advances in Radiation Oncology, Cancer, Clinical Cancer Research and World Neurosurgery.

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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