Jing Yan

1.6k citations
68 papers · 1.0k indexed · h-index 17

Impact in

Papers in

Jing Yan

63 papers receiving 1.0k citations

Peers

Jing Yan
Comparison fields: 5 of 162
  • Hardware and Architecture 93
  • Geriatrics and Gerontology 42
  • Health Information Management 47
  • Critical Care and Intensive Care Medicine 48
  • Computer Vision and Pattern Recognition 151
Replace V. Rajesh with:
V. Rajesh India
Amit Gupta India
Alex Bui United States
Yun Cheng China
Seung Min Park South Korea
Faisal Rehman Pakistan
Stephen Bonner United Kingdom
You Chen United States
Jing Yan relative to V. Rajesh India V. Rajesh's profile →
Citations per field
00.5×
V. Rajesh · 1×
Citations per year

Countries citing papers authored by Jing Yan

Since Specialization
Citations

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

Fields of papers citing papers by Jing Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20241
4 20231
5 20231
6 202320
7 202230
8 20220
9 202110
10 20213
11 202119
12 202111
13 20202
14 202067
15 201926
16 201919
17 201511
18
A computational model for heart failure stratification
20113
19 201119
20
An improved Bayesian network structure learning algorithm and its application in an intelligent B2C portal
20074

About Jing Yan

Jing Yan is a scholar working on Critical Care and Intensive Care Medicine, Health Information Management, Nephrology, Internal Medicine and Artificial Intelligence, having authored 68 papers that have together received 1.0k indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (10 papers), Respiratory Support and Mechanisms (8 papers), Algorithms and Data Compression (7 papers), Data Mining Algorithms and Applications (5 papers), Artificial Intelligence in Healthcare (4 papers), Intensive Care Unit Cognitive Disorders (4 papers), Rough Sets and Fuzzy Logic (3 papers) and Neural Networks and Applications (3 papers). The work is most often cited by research in Hardware and Architecture (93 citations), Geriatrics and Gerontology (42 citations), Health Information Management (47 citations), Critical Care and Intensive Care Medicine (48 citations) and Computer Vision and Pattern Recognition (151 citations). Jing Yan has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Guolong Cai, Ningyi Xu, Yu Wang, Gangmin Ning, Jing Xia, Molei Yan, Min Zhu, Li Li, Feng-hsiung Hsu and Bo Wang. Their work appears in journals such as Frontiers in Medicine, Medicine, Frontiers in Pharmacology, Scientific Reports and Annals of Palliative Medicine.

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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