Hak Hee Kim

6.4k citations
215 papers · 4.5k · 1 hit paper · h-index 35

Impact in

Papers in

Hak Hee Kim

202 papers receiving 4.4k citations

Hak Hee Kim's Hit Papers

Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study 2020 · 337 citations
3370+2+4Years since publication100200300

Peers

Hak Hee Kim
Comparison fields: 5 of 139
  • Health Informatics 96
  • Cancer Research 896
  • Radiology, Nuclear Medicine and Imaging 1.3k
  • Pathology and Forensic Medicine 755
  • Oncology 638
Replace Zaibo Li with:
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Hak Hee Kim relative to Zaibo Li United States Zaibo Li's profile →
Citations per field
00.5×3.5×
Zaibo Li · 1×
Citations per year

Countries citing papers authored by Hak Hee Kim

Since Specialization
Citations

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

Fields of papers citing papers by Hak Hee Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 215 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study
Hit paper breakdown →
2020337
2 2006296
3 2013152
4 2017124
5 2003116
6 2001110
7 200881
8 201574
9 201172
10 201369
11 201163
12 201258
13 201356
14 201155
15 201955
16 200853
17 201352
18 200852
19 201752
20 200948

About Hak Hee Kim

Hak Hee Kim is a scholar working on Radiology, Nuclear Medicine and Imaging, Pathology and Forensic Medicine, Cancer Research, Pulmonary and Respiratory Medicine and Surgery, having authored 215 papers that have together received 4.5k indexed citations. Recurring topics across this work include Breast Lesions and Carcinomas (51 papers), MRI in cancer diagnosis (39 papers), Breast Cancer Treatment Studies (39 papers), Digital Radiography and Breast Imaging (31 papers), Radiomics and Machine Learning in Medical Imaging (18 papers), AI in cancer detection (17 papers), Breast Implant and Reconstruction (15 papers) and Medical Imaging Techniques and Applications (13 papers). The work is most often cited by research in Health Informatics (96 citations), Cancer Research (896 citations), Radiology, Nuclear Medicine and Imaging (1.3k citations), Pathology and Forensic Medicine (755 citations) and Oncology (638 citations). Hak Hee Kim has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Hee Jung Shin, Joo Hee, Eun Young Chae, Woo Jung Choi, Gyungyub Gong, Sung‐Bae Kim, Soonmoon Yoo, Boo‐Kyung Han, Mi-Jung Kim and Eun‐Kyung Kim. Their work appears in journals such as American Journal of Roentgenology, Acta Radiologica, Radiology, European Radiology and Scientific Reports.

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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