Lingying Wu

3.3k citations
207 papers · 1.8k · h-index 22

Impact in

Papers in

Lingying Wu

199 papers receiving 1.8k citations

Peers

Lingying Wu
Comparison fields: 5 of 105
  • Obstetrics and Gynecology 366
  • Reproductive Medicine 336
  • Cancer Research 251
  • Oncology 395
  • Molecular Biology 436
Replace Danhua Shen with:
Danhua Shen China
Beihua Kong China
Salvatore Lopez Italy
Marta A. Crispens United States
Sohei Yamamoto Japan
Eirini Pectasides Greece
Yasuyuki Hirashima Japan
Pamela J. Paley United States
A Fanucchi Italy
Jesus Paula Carvalho Brazil
Lingying Wu relative to Danhua Shen China Danhua Shen's profile →
Citations per field
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Citations per year

Countries citing papers authored by Lingying Wu

Since Specialization
Citations

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

Fields of papers citing papers by Lingying Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 207 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202185
2 202276
3 200766
4 201757
5 202253
6 201642
7 201438
8 201538
9 201231
10 202229
11
A pilot study of sentinel lymph nodes identification in patients with endometrial cancer.
200729
12 202027
13 201726
14 202126
15 201225
16 200925
17 201724
18 202224
19 201423
20 202423

About Lingying Wu

Lingying Wu is a scholar working on Oncology, Obstetrics and Gynecology, Reproductive Medicine, Molecular Biology and Pulmonary and Respiratory Medicine, having authored 207 papers that have together received 1.8k indexed citations. Recurring topics across this work include Ovarian cancer diagnosis and treatment (37 papers), Endometrial and Cervical Cancer Treatments (37 papers), PARP inhibition in cancer therapy (18 papers), Pelvic floor disorders treatments (9 papers), Cervical Cancer and HPV Research (7 papers), Cancer-related molecular mechanisms research (7 papers), Cancer Immunotherapy and Biomarkers (7 papers) and Cancer Genomics and Diagnostics (6 papers). The work is most often cited by research in Obstetrics and Gynecology (366 citations), Reproductive Medicine (336 citations), Cancer Research (251 citations), Oncology (395 citations) and Molecular Biology (436 citations). Lingying Wu has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Ning Li, Jusheng An, Jia Zeng, Leilei Liang, Xiaoguang Li, Guangwen Yuan, Jian Li, Bin Li, Hong‐Tu Zhang and Tiantian Wang. Their work appears in journals such as Journal of Clinical Oncology, Gynecologic Oncology, International Journal of Gynecological Cancer, Frontiers in Oncology and Annals of Oncology.

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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