Lu Gao

2.7k citations
112 papers · 1.8k indexed · h-index 25

Impact in

Papers in

Lu Gao

108 papers receiving 1.7k citations

Peers

Lu Gao
Comparison fields: 5 of 149
  • Endocrinology, Diabetes and Metabolism 480
  • Nephrology 171
  • Genetics 218
  • Cancer Research 268
  • Critical Care and Intensive Care Medicine 44
Replace Lin Liu with:
Lin Liu China
Klaus‐Martin Schulte Germany
Markus Metzler Germany
Fiemu E. Nwariaku United States
Ulrich M. Vischer Switzerland
Stella Bernardi Italy
Paula K. Shireman United States
Xun Zhang Canada
Luca Dalle Carbonare Italy
Hiromichi Suzuki Japan
Lu Gao relative to Lin Liu China Lin Liu's profile →
Citations per field
00.5×1.5×2.1×
Lin Liu · 1×
Citations per year

Countries citing papers authored by Lu Gao

Since Specialization
Citations

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

Fields of papers citing papers by Lu Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20240
3 20231
4 20237
5 20238
6 20234
7 20231
8 202215
9 202129
10 20216
11 20204
12 201911
13
Practice of blended teaching in the teaching of systematic anatomy
20190
14 201928
15 20183
16 201814
17 201827
18 201741
19 201646
20
Effect of different lipid diets on the growth of juvenile Acipenser schrenckii
20043

About Lu Gao

Lu Gao is a scholar working on Endocrinology, Diabetes and Metabolism, Genetics, Nephrology, Modeling and Simulation and Health Informatics, having authored 112 papers that have together received 1.8k indexed citations. Recurring topics across this work include Pituitary Gland Disorders and Treatments (45 papers), Growth Hormone and Insulin-like Growth Factors (24 papers), Glioma Diagnosis and Treatment (15 papers), Adrenal and Paraganglionic Tumors (13 papers), TGF-β signaling in diseases (7 papers), Acute Kidney Injury Research (6 papers), Ferroptosis and cancer prognosis (6 papers) and Ophthalmology and Eye Disorders (5 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (480 citations), Nephrology (171 citations), Genetics (218 citations), Cancer Research (268 citations) and Critical Care and Intensive Care Medicine (44 citations). Lu Gao has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Bing Xing, Xiaopeng Guo, Zihao Wang, Wei Lian, Kan Deng, Chenzhe Feng, Yinghui Wang, Zihao Wang, Wenbin Ma and Yong‐Guang Yang. Their work appears in journals such as World Neurosurgery, Frontiers in Endocrinology, Frontiers in Oncology, BMC Nephrology and The Journal of Clinical Endocrinology & Metabolism.

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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