Hong Kang

2.3k total citations · 2 hit papers
41 papers, 1.2k citations indexed

About

Hong Kang is a scholar working on Health Information Management, Emergency Medical Services and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Hong Kang has authored 41 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Health Information Management, 12 papers in Emergency Medical Services and 11 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Hong Kang's work include Electronic Health Records Systems (14 papers), Patient Safety and Medication Errors (12 papers) and Retinal Imaging and Analysis (11 papers). Hong Kang is often cited by papers focused on Electronic Health Records Systems (14 papers), Patient Safety and Medication Errors (12 papers) and Retinal Imaging and Analysis (11 papers). Hong Kang collaborates with scholars based in United States, China and Hong Kong. Hong Kang's co-authors include Kai Wang, Tao Li, Song Guo, Hanruo Liu, Yingqi Gao, Yang Gong, Huazhu Fu, Bo Wang, Yujun Zhang and Chunyu Hu and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Medical Imaging and Information Sciences.

In The Last Decade

Hong Kang

40 papers receiving 1.2k citations

Hit Papers

Diagnostic assessment of deep learning algorithms for dia... 2019 2026 2021 2023 2019 2021 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Diagnostic assessment of deep learning algorithms for diabetic retinopathy screening
    2019 355 citations Tao Li, Yingqi Gao et al. Information Sciences profile →
  2. Applications of deep learning in fundus images: A review
    2021 227 citations Tao Li, Bo Wang et al. Medical Image Analysis profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hong Kang United States 13 859 583 452 192 125 41 1.2k
Deborah Broadbent United Kingdom 15 1.3k 1.5× 1.2k 2.0× 326 0.7× 196 1.0× 92 0.7× 28 1.6k
Yusuke Kawasumi Japan 12 256 0.3× 22 0.0× 21 0.0× 120 0.6× 81 0.6× 45 570
Taehoon Ko South Korea 13 161 0.2× 83 0.1× 35 0.1× 67 0.3× 123 1.0× 42 606
Bo Jin China 18 60 0.1× 10 0.0× 83 0.2× 125 0.7× 335 2.7× 52 1.0k
Michelle R. Hribar United States 17 125 0.1× 83 0.1× 12 0.0× 380 2.0× 107 0.9× 70 954
Omolola Ogunyemi United States 16 128 0.1× 97 0.2× 18 0.0× 480 2.5× 292 2.3× 42 974
Yilin Ning Singapore 17 104 0.1× 33 0.1× 12 0.0× 89 0.5× 230 1.8× 58 822
David C. Kale United States 11 130 0.2× 8 0.0× 52 0.1× 179 0.9× 467 3.7× 16 943
Mehmet Aydar United States 8 274 0.3× 9 0.0× 27 0.1× 189 1.0× 226 1.8× 18 1.1k
Nida Shahid Canada 6 71 0.1× 21 0.0× 24 0.1× 51 0.3× 84 0.7× 18 422

Countries citing papers authored by Hong Kang

Since Specialization
Citations

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

Fields of papers citing papers by Hong Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hong Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Hong Kang. A scholar is included among the top collaborators of Hong Kang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hong Kang. Hong Kang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wu, Yanlin, et al.. (2024). Trans-SAM: Transfer Segment Anything Model to medical image segmentation with Parameter-Efficient Fine-Tuning. Knowledge-Based Systems. 310. 112909–112909. 4 indexed citations
2.
Zhang, Yue, Ruyue Li, Tao Li, et al.. (2022). Cost-Utility Analysis of Screening for Diabetic Retinopathy in China. SHILAP Revista de lepidopterología. 2022. 9832185–9832185. 2 indexed citations
3.
Li, Tao, Bo Wang, Chunyu Hu, et al.. (2021). Applications of deep learning in fundus images: A review. Medical Image Analysis. 69. 101971–101971. 227 indexed citations breakdown →
4.
Kang, Hong & Yang Gong. (2020). Creating a database for health IT events via a hybrid deep learning model. Journal of Biomedical Informatics. 110. 103556–103556. 9 indexed citations
5.
Kang, Hong, Yingqi Gao, Song Guo, et al.. (2020). AVNet: A retinal artery/vein classification network with category-attention weighted fusion. Computer Methods and Programs in Biomedicine. 195. 105629–105629. 24 indexed citations
6.
Li, Tao, Yingqi Gao, Kai Wang, et al.. (2019). Diagnostic assessment of deep learning algorithms for diabetic retinopathy screening. Information Sciences. 501. 511–522. 355 indexed citations breakdown →
7.
Guo, Song, Tao Li, Hong Kang, et al.. (2019). L-Seg: An end-to-end unified framework for multi-lesion segmentation of fundus images. Neurocomputing. 349. 52–63. 98 indexed citations
8.
Guo, Song, Kai Wang, Hong Kang, et al.. (2019). Bin loss for hard exudates segmentation in fundus images. Neurocomputing. 392. 314–324. 34 indexed citations
9.
Kang, Hong & Yang Gong. (2019). Creating a Database for Health IT Event Reports by Using a Hybrid Deep Learning Model.. AMIA. 1 indexed citations
10.
Guo, Song, Kai Wang, Hong Kang, et al.. (2019). BTS-DSN: Deeply supervised neural network with short connections for retinal vessel segmentation. International Journal of Medical Informatics. 126. 105–113. 130 indexed citations
11.
Kang, Hong, et al.. (2019). Scoring Patient Fall Reports Using Quality Rubric and Machine Learning. Studies in health technology and informatics. 264. 639–643. 7 indexed citations
12.
Liang, Chen, et al.. (2019). Leveraging Patient Safety Research: Efforts Made Fifteen Years Since To Err Is Human. Studies in health technology and informatics. 264. 983–987. 5 indexed citations
13.
Wang, Jing, et al.. (2019). Mobile and Connected Health Technology Needs for Older Adults Aging in Place: Cross-Sectional Survey Study. JMIR Aging. 2(1). e13864–e13864. 32 indexed citations
14.
Gong, Yang, et al.. (2019). Accurate and rapid screening model for potential diabetes mellitus. BMC Medical Informatics and Decision Making. 19(1). 41–41. 23 indexed citations
15.
Kang, Hong, et al.. (2019). Examining Reproducibility of Literature Search in Meta-Analysis. Studies in health technology and informatics. 264. 228–232.
16.
Kang, Hong, et al.. (2019). Data Quality Assessment of Narrative Medication Error Reports. Studies in health technology and informatics. 265. 101–106. 1 indexed citations
17.
Kang, Hong, Ju Wang, Bin Yao, Sicheng Zhou, & Yang Gong. (2018). Toward safer health care: a review strategy of FDA medical device adverse event database to identify and categorize health information technology related events. JAMIA Open. 2(1). 179–186. 12 indexed citations
18.
Yao, Bin, et al.. (2017). Leveraging Event Reporting Through Knowledge Support: A Knowledge-Based Approach to Promoting Patient Fall Prevention. Studies in health technology and informatics. 245. 973–977. 3 indexed citations
19.
Kang, Hong, et al.. (2017). Enhancing Patient Safety Event Reporting. Applied Clinical Informatics. 8(3). 893–909. 35 indexed citations
20.
Kang, Hong & Yang Gong. (2017). Developing a similarity searching module for patient safety event reporting system using semantic similarity measures. BMC Medical Informatics and Decision Making. 17(S2). 75–75. 5 indexed citations

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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