Jun Lyu

315 papers receiving 6.4k citations

Hit Papers

Data mining in clinical big data: the frequently used databases, steps, and methodological models 2021 · 327 citations
3272019202620212023250500750

Peers

Jun Lyu
Comparison fields: 5 of 187
  • Biological Psychiatry 210
  • Critical Care and Intensive Care Medicine 268
  • Oncology 1.1k
  • Nephrology 286
  • Otorhinolaryngology 166
Replace Lin Zhang with:
Lin Zhang China
Fabián Sanchis‐Gomar Spain
Ioanna Tzoulaki United Kingdom
Xiaoping Miao China
Juhee Cho South Korea
Liping Zhang China
Chuanzhu Yan China
Amanda Lee United Kingdom
Xiao Shang China
Adrían V. Hernández United States
Jun Lyu relative to Lin Zhang China Lin Zhang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jun Lyu

Since Specialization
Citations

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

Fields of papers citing papers by Jun Lyu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 353 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Changes in the global burden of depression from 1990 to 2017: Findings from the Global Burden of Disease study
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2019926
2
Brief introduction of medical database and data mining technology in big data era
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2020369
3
Data mining in clinical big data: the frequently used databases, steps, and methodological models
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2021327
4 2020217
5 2020215
6 2020175
7 2020167
8 2020131
9 2020123
10 202298
11 202092
12 201590
13 201983
14 202075
15 202268
16 202166
17 202364
18 202059
19 202358
20 202255

About Jun Lyu

Jun Lyu is a scholar working on Critical Care and Intensive Care Medicine, Nephrology, Oncology, Epidemiology and Geriatrics and Gerontology, having authored 353 papers that have together received 6.5k indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (47 papers), Intensive Care Unit Cognitive Disorders (21 papers), Hemodynamic Monitoring and Therapy (16 papers), Colorectal Cancer Screening and Detection (15 papers), Pancreatic and Hepatic Oncology Research (14 papers), Global Cancer Incidence and Screening (13 papers), Nutritional Studies and Diet (13 papers) and Respiratory Support and Mechanisms (11 papers). The work is most often cited by research in Biological Psychiatry (210 citations), Critical Care and Intensive Care Medicine (268 citations), Oncology (1.1k citations), Nephrology (286 citations) and Otorhinolaryngology (166 citations). Jun Lyu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Hairong He, Qingqing Liu, Fanfan Zhao, Xiaojie Feng, Yang Jin, Aozi Feng, Tao Huang, Shuai Zheng, Li Li and Jin Yang. Their work appears in journals such as Frontiers in Medicine, Frontiers in Pharmacology, Cancer Control, Cancer Medicine and Frontiers in Cardiovascular 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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