Chia‐Te Liao

1.1k citations
78 papers · 688 · h-index 13

Impact in

Papers in

Chia‐Te Liao

70 papers receiving 673 citations

Peers

Chia‐Te Liao
Comparison fields: 5 of 118
  • Cardiology and Cardiovascular Medicine 187
  • Nephrology 57
  • Health Informatics 9
  • Endocrinology, Diabetes and Metabolism 66
  • Infectious Diseases 58
Replace Jun Guo with:
Jun Guo China
Christopher C. Cheung Canada
Ahmet İlker Tekkeşin Türkiye
Pierre Qian Australia
Hyunsun Lim South Korea
Syed N. Rahman United States
Seok‐Jae Heo South Korea
Fu‐Chun Chiu Taiwan
Raphael Romano Bruno Germany
Ji Hoon Kim South Korea
Chia‐Te Liao relative to Jun Guo China Jun Guo's profile →
Citations per field
00.5×2.6×
Jun Guo · 1×
Citations per year

Countries citing papers authored by Chia‐Te Liao

Since Specialization
Citations

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

Fields of papers citing papers by Chia‐Te Liao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chia‐Te Liao. 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 Chia‐Te Liao. The network helps show where Chia‐Te Liao may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202099
2 202166
3 200859
4 202231
5 202130
6 202225
7 202322
8 201021
9 202020
10 202019
11 202118
12 202215
13 202312
14 202212
15 202211
16 202010
17 202310
18 20219
19 20139
20 20129

About Chia‐Te Liao

Chia‐Te Liao is a scholar working on Cardiology and Cardiovascular Medicine, Computer Vision and Pattern Recognition, Surgery, Endocrinology, Diabetes and Metabolism and Infectious Diseases, having authored 78 papers that have together received 688 indexed citations. Recurring topics across this work include Heart Failure Treatment and Management (11 papers), Face and Expression Recognition (7 papers), Blood Pressure and Hypertension Studies (5 papers), Face recognition and analysis (5 papers), HIV-related health complications and treatments (5 papers), Diabetes Treatment and Management (4 papers), Dialysis and Renal Disease Management (3 papers) and COVID-19 Clinical Research Studies (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (187 citations), Nephrology (57 citations), Health Informatics (9 citations), Endocrinology, Diabetes and Metabolism (66 citations) and Infectious Diseases (58 citations). Chia‐Te Liao has collaborated with scholars based in Taiwan, Belgium and United States. Frequent co-authors include Wei‐Ting Chang, Han Siong Toh, Wen‐Liang Yu, Shang‐Hong Lai, Yuh‐Feng Lin, Hung‐Yu Chang, Yung-Ho Hsu, Hui‐Wen Chiu, Hung-Jin Huang and Zhih‐Cherng Chen. Their work appears in journals such as Frontiers in Cardiovascular Medicine, ESC Heart Failure, Medicine, Cardiovascular Drugs and Therapy 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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