Chang‐Min Kim

1.7k citations
68 papers · 1.4k · h-index 21

Impact in

  • Hepatology top 1%
    • Hepatocellular Carcinoma Treatment and Prognosis
    • Hepatitis C virus research
    • Cancer, Hypoxia, and Metabolism

Papers in

Chang‐Min Kim

54 papers receiving 1.3k citations

Peers

Chang‐Min Kim
Comparison fields: 5 of 122
  • Hepatology 598
  • Cancer Research 175
  • Pathology and Forensic Medicine 178
  • Epidemiology 331
  • Oncology 217
Replace Yanhong Wang with:
Yanhong Wang China
Du He China
Masaaki Oka Japan
Heng Pan United States
Seiya Momosaki Japan
Yuqiang Cheng China
Hiroyuki Okuda Japan
Ruoyu Wang China
Wei‐Ping Lee Taiwan
Qian Kang China
Chang‐Min Kim relative to Yanhong Wang China Yanhong Wang's profile →
Citations per field
00.5×1.5×
Yanhong Wang · 1×
Citations per year

Countries citing papers authored by Chang‐Min Kim

Since Specialization
Citations

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

Fields of papers citing papers by Chang‐Min Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chang‐Min 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 Chang‐Min Kim. The network helps show where Chang‐Min Kim may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008199
2 2007113
3 200371
4 200569
5 202367
6 200764
7 201353
8 200552
9 200346
10 200845
11 200742
12 200435
13 200633
14 202330
15 200829
16 201128
17 200525
18 202125
19 199321
20 202021

About Chang‐Min Kim

Chang‐Min Kim is a scholar working on Hepatology, Molecular Biology, Epidemiology, Artificial Intelligence and Information Systems, having authored 68 papers that have together received 1.4k indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (11 papers), Hepatitis B Virus Studies (8 papers), AI in cancer detection (6 papers), Hepatitis C virus research (6 papers), Microtubule and mitosis dynamics (5 papers), Education, Safety, and Science Studies (5 papers), Education and Learning Interventions (4 papers) and Liver Disease Diagnosis and Treatment (4 papers). The work is most often cited by research in Hepatology (598 citations), Cancer Research (175 citations), Pathology and Forensic Medicine (178 citations), Epidemiology (331 citations) and Oncology (217 citations). Chang‐Min Kim has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Joong‐Won Park, Woo Jin Lee, Ju Hyun Shim, Joon‐Il Choi, Sun‐Young Kong, Kyung Woo Park, Chang‐Woo Lee, Kwan‐Hyuck Baek, Ji Hoon Kim and Hyun Beom Kim. Their work appears in journals such as Applied Sciences, IEEE Access, Journal of Cancer Research and Clinical Oncology, Japanese Journal of Clinical Oncology and Cancer Research.

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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