Te‐Fu Chan

2.7k citations
91 papers · 2.3k · h-index 26

Impact in

Papers in

Te‐Fu Chan

89 papers receiving 2.2k citations

Peers

Te‐Fu Chan
Comparison fields: 5 of 96
  • Obstetrics and Gynecology 245
  • Reproductive Medicine 121
  • Pharmaceutical Science 63
  • Genetics 65
  • Epidemiology 178
Replace Ricardo de Carvalho Cavalli with:
Ricardo de Carvalho Cavalli Brazil
Ivano Raimondo Italy
Ying Fang Zhou China
Serge Rozenberg Belgium
Joanna Mitri United States
Pasquale DE FRANCISCIS Italy
Yuan He China
Carlos Antônio Negrato Brazil
Vanessa Jordan New Zealand
Susan Nayfield United States
Te‐Fu Chan relative to Ricardo de Carvalho Cavalli Brazil Ricardo de Carvalho Cavalli's profile →
Citations per field
00.5×2×4×6×8.1×
Ricardo de Carvalho Cavalli · 1×
Citations per year

Countries citing papers authored by Te‐Fu Chan

Since Specialization
Citations

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

Fields of papers citing papers by Te‐Fu Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Te‐Fu Chan. 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 Te‐Fu Chan. The network helps show where Te‐Fu Chan may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020130
2 2014113
3 2006108
4 200797
5 201483
6 200481
7 200781
8 200775
9 200468
10 200367
11 201263
12 201663
13
Health promoting lifestyles and related factors in pregnant women.
201061
14 200759
15 200754
16 200948
17 201648
18 200945
19 200344
20 201138

About Te‐Fu Chan

Te‐Fu Chan is a scholar working on Obstetrics and Gynecology, Reproductive Medicine, Pediatrics, Perinatology and Child Health, Pharmaceutical Science and Public Health, Environmental and Occupational Health, having authored 91 papers that have together received 2.3k indexed citations. Recurring topics across this work include Gestational Diabetes Research and Management (8 papers), Pregnancy and preeclampsia studies (4 papers), Esophageal Cancer Research and Treatment (4 papers), Ovarian function and disorders (4 papers), Cervical Cancer and HPV Research (3 papers), Diet, Metabolism, and Disease (3 papers), Advancements in Transdermal Drug Delivery (3 papers) and Pregnancy and Medication Impact (3 papers). The work is most often cited by research in Obstetrics and Gynecology (245 citations), Reproductive Medicine (121 citations), Pharmaceutical Science (63 citations), Genetics (65 citations) and Epidemiology (178 citations). Te‐Fu Chan has collaborated with scholars based in Taiwan, United States and Japan. Frequent co-authors include Chien-Hung Lee, Eing‐Mei Tsai, Fan‐Hao Chou, Shiang‐Bin Jong, Hsiao‐Ling Huang, Yi‐Ling Chen, Chun‐Ying Lee, Chich‐Hsiu Hung, Shyng‐Shiou F. Yuan and Jinu‐Huang Su. Their work appears in journals such as Fertility and Sterility, International Journal of Cancer, Acta Obstetricia Et Gynecologica Scandinavica, Gynecologic and Obstetric Investigation and Cells.

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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