Hsin‐Ying Lu

822 citations
27 papers · 584 · h-index 12

Impact in

Papers in

Hsin‐Ying Lu

26 papers receiving 563 citations

Peers

Hsin‐Ying Lu
Comparison fields: 5 of 84
  • Anesthesiology and Pain Medicine 139
  • Obstetrics and Gynecology 134
  • Reproductive Medicine 54
  • Pharmacology 43
  • Health Informatics 6
Replace G. Shorten with:
G. Shorten Ireland
Christina Jang Australia
L. Faerber Germany
Alese Wagner Canada
Pak Cheung Chan Canada
J. H. Cort Czechia
Katina Aleksovska Italy
Robert Metz United States
A. Pettersson Sweden
Gayatri Vishwakarma India
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Citations per field
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Citations per year

Countries citing papers authored by Hsin‐Ying Lu

Since Specialization
Citations

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

Fields of papers citing papers by Hsin‐Ying Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hsin‐Ying Lu. 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 Hsin‐Ying Lu. The network helps show where Hsin‐Ying Lu may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006217
2 201978
3 201641
4 201931
5 202128
6 201227
7 201920
8 202119
9 202217
10 201816
11 201612
12 202311
13 202410
14 20179
15 20189
16 20196
17 20225
18 20225
19 20215
20 20194

About Hsin‐Ying Lu

Hsin‐Ying Lu is a scholar working on Obstetrics and Gynecology, Surgery, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Cancer Research, having authored 27 papers that have together received 584 indexed citations. Recurring topics across this work include Endometrial and Cervical Cancer Treatments (6 papers), Ovarian cancer diagnosis and treatment (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Aortic aneurysm repair treatments (2 papers), Abdominal vascular conditions and treatments (2 papers), Hyperglycemia and glycemic control in critically ill and hospitalized patients (1 paper), Dental Implant Techniques and Outcomes (1 paper) and Renal and Vascular Pathologies (1 paper). The work is most often cited by research in Anesthesiology and Pain Medicine (139 citations), Obstetrics and Gynecology (134 citations), Reproductive Medicine (54 citations), Pharmacology (43 citations) and Health Informatics (6 citations). Hsin‐Ying Lu has collaborated with scholars based in Taiwan, United States and Japan. Frequent co-authors include Tsong‐Hai Lee, Gigin Lin, Chun‐Hua Wang, Shang‐Hung Lin, Allan Concejero, Chyong‐Huey Lai, Yu‐Ting Huang, Yu‐Chun Lin, Shu‐Hang Ng and Koon‐Kwan Ng. Their work appears in journals such as European Radiology, Cancer Imaging, Journal of Magnetic Resonance Imaging, PLoS ONE and Anaesthesia.

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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