Ling-Sha Ju

28 papers receiving 667 citations

Peers

Ling-Sha Ju
Comparison fields: 5 of 105
  • Developmental Neuroscience 244
  • Critical Care and Intensive Care Medicine 173
  • Biological Psychiatry 70
  • Anesthesiology and Pain Medicine 97
  • Behavioral Neuroscience 35
Replace Changwei Wei with:
Changwei Wei China
Zongze Zhang China
Eric L. Goldwaser United States
Jiangyan Xia China
Jing Dai China
Tetsuhiro Sakai Japan
Ju Zou China
Hanwen Gu China
Lifeng Wang China
Veronica Fagerholm Finland
Ling-Sha Ju relative to Changwei Wei China Changwei Wei's profile →
Citations per field
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Citations per year

Countries citing papers authored by Ling-Sha Ju

Since Specialization
Citations

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

Fields of papers citing papers by Ling-Sha Ju

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ling-Sha Ju. 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 Ling-Sha Ju. The network helps show where Ling-Sha Ju may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202078
2 201567
3 201856
4 201550
5 201649
6 202346
7 201846
8 201937
9 201732
10 202225
11 201924
12 201721
13 201520
14 202317
15 201714
16 201913
17 201811
18 202010
19 20209
20 20238

About Ling-Sha Ju

Ling-Sha Ju is a scholar working on Developmental Neuroscience, Critical Care and Intensive Care Medicine, Anesthesiology and Pain Medicine, Pharmacology and Neurology, having authored 32 papers that have together received 676 indexed citations. Recurring topics across this work include Anesthesia and Neurotoxicity Research (19 papers), Intensive Care Unit Cognitive Disorders (10 papers), Anesthesia and Sedative Agents (8 papers), Traumatic Brain Injury and Neurovascular Disturbances (2 papers), Cardiac, Anesthesia and Surgical Outcomes (2 papers), Tryptophan and brain disorders (2 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Developmental Neuroscience (244 citations), Critical Care and Intensive Care Medicine (173 citations), Biological Psychiatry (70 citations), Anesthesiology and Pain Medicine (97 citations) and Behavioral Neuroscience (35 citations). Ling-Sha Ju has collaborated with scholars based in China, United States and India. Frequent co-authors include Jianjun Yang, Anatoly E. Martynyuk, Timothy E. Morey, Mu‐Huo Ji, Cheng-Mao Zhou, Jianhua Tong, Jiaojiao Yang, Nikolaus Gravenstein, Christoph N. Seubert and Min Jia. Their work appears in journals such as Anesthesiology, Biology, BMC Psychiatry, Anesthesia & Analgesia and Journal of Neurotrauma.

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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