Edward Choi

7.2k total citations · 3 hit papers
48 papers, 2.5k citations indexed

About

Edward Choi is a scholar working on Artificial Intelligence, Health Information Management and Computer Vision and Pattern Recognition. According to data from OpenAlex, Edward Choi has authored 48 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 6 papers in Health Information Management and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Edward Choi's work include Topic Modeling (15 papers), Machine Learning in Healthcare (14 papers) and Artificial Intelligence in Healthcare (6 papers). Edward Choi is often cited by papers focused on Topic Modeling (15 papers), Machine Learning in Healthcare (14 papers) and Artificial Intelligence in Healthcare (6 papers). Edward Choi collaborates with scholars based in United States, South Korea and Canada. Edward Choi's co-authors include Jimeng Sun, Walter F. Stewart, Cao Xiao, Mohammad Taha Bahadori, Le Song, Young‐Hak Kim, Jaegul Choo, Youngbin Kim, Bum Chul Kwon and Minje Choi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Scientific Reports and PLoS Medicine.

In The Last Decade

Edward Choi

43 papers receiving 2.5k citations

Hit Papers

Using recurrent neural network models for early detection... 2016 2026 2019 2022 2016 2018 2017 100 200 300 400 500

Peers

Edward Choi
Comparison fields: 5 of 158
  • Artificial Intelligence 1.8k
  • Health Information Management 713
  • Computer Vision and Pattern Recognition 361
  • Molecular Biology 330
  • Radiology, Nuclear Medicine and Imaging 273
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Citations per field, relative to Edward Choi
Edward Choi · 1×
Citations per year, relative to Edward Choi
Edward Choi · 1×

Countries citing papers authored by Edward Choi

Since Specialization
Citations

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

Fields of papers citing papers by Edward Choi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Edward Choi

This figure shows the co-authorship network connecting the top 25 collaborators of Edward Choi. A scholar is included among the top collaborators of Edward Choi 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 Edward Choi. Edward Choi 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
# Work Indexed citations
1 2
2 2
3 8
4 3
5 22
6 4
7 13
8 23
9 9
10 7
11 3
12 131
13 32
14 27
15 81
16
Compositional Obverter Communication Learning From Raw Visual Input
3
17
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
46
18
Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networks.
24
19
Generating Multi-label Discrete Patient Records using Generative Adversarial Networks
24
20 57

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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