Y.-T. Gao

1.2k citations
14 papers · 795 · h-index 11

Impact in

Papers in

Y.-T. Gao

14 papers receiving 765 citations

Peers

Y.-T. Gao
Comparison fields: 5 of 87
  • Endocrinology, Diabetes and Metabolism 210
  • Cancer Research 176
  • Oncology 278
  • Pulmonary and Respiratory Medicine 198
  • Physiology 113
Replace Bimin Shi with:
Bimin Shi China
Kirk Snyder United States
Ting‐Yuan David Cheng United States
Sang Yong Kim South Korea
Sheetal Hardikar United States
X-O Shu China
Akihisa Hidaka Japan
Abraham M. Y. Nomura United States
Shih-Chen Chang United States
Seung Jun Kim South Korea
Y.-T. Gao relative to Bimin Shi China Bimin Shi's profile →
Citations per field
00.5×3.4×
Bimin Shi · 1×
Citations per year

Countries citing papers authored by Y.-T. Gao

Since Specialization
Citations

This map shows the geographic impact of Y.-T. 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 Y.-T. Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Y.-T. Gao more than expected).

Fields of papers citing papers by Y.-T. Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 2002195
2
Insulin-like growth factors and prostate cancer: a population-based case-control study in China.
2001152
3
Body size and prostate cancer: a population-based case-control study in China.
2000122
4 201662
5 200658
6
Relation of obesity and body fat distribution to endometrial cancer in Shanghai, China.
199247
7 200742
8 201335
9
Helicobacter pylori infection and risk of gastric cancer in Shanghai, China: updated results based upon a locally developed and validated assay and further follow-up of the cohort.
199935
10 201518
11
Cancer survival in Shanghai, People's Republic of China.
199813
12 20248
13 20217
14 20241

About Y.-T. Gao

Y.-T. Gao is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Oncology, Surgery and Obstetrics and Gynecology, having authored 14 papers that have together received 795 indexed citations. Recurring topics across this work include Cancer Risks and Factors (3 papers), Nutritional Studies and Diet (2 papers), Endometrial and Cervical Cancer Treatments (2 papers), Ovarian cancer diagnosis and treatment (2 papers), Prostate Cancer Treatment and Research (2 papers), Gastric Cancer Management and Outcomes (1 paper), Metabolism, Diabetes, and Cancer (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (210 citations), Cancer Research (176 citations), Oncology (278 citations), Pulmonary and Respiratory Medicine (198 citations) and Physiology (113 citations). Y.-T. Gao has collaborated with scholars based in China, United States and Vietnam. Frequent co-authors include Ann W. Hsing, Frank Z. Stanczyk, Streamson C. Chua, Jie Deng, Isabell A. Sesterhenn, Tao Xie, F. Kash Mostofi, Jie Deng, Jing Deng and Jacques Bénichou. Their work appears in journals such as Carcinogenesis, Annals of Oncology, JNCI Journal of the National Cancer Institute, Medicine and International Journal of Epidemiology.

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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