Yun‐Ju Lai

2.0k citations
95 papers · 1.5k indexed · h-index 21
Topics
Pregnancy and preeclampsia studies (11 papers)Obesity, Physical Activity, Diet (9 papers)Diabetes, Cardiovascular Risks, and Lipoproteins (9 papers)

In The Last Decade

Yun‐Ju Lai

92 papers receiving 1.4k citations

Peers

Yun‐Ju Lai
Comparison fields: 5 of 126
  • Epidemiology 349
  • Public Health, Environmental and Occupational Health 248
  • Physiology 240
  • Pediatrics, Perinatology and Child Health 186
  • Endocrinology, Diabetes and Metabolism 165
Replace Masoud Rahmati with:
Masoud Rahmati Iran
Alan D. Penman United States
Pedro Muñoz Spain
Magdalena Olszanecka‐Glinianowicz Poland
Renate T. de Jongh Netherlands
Scott Segal United States
Vanesa Bellou Greece
Hongpeng Sun China
Cristina Pellegrino Baena Brazil
José I. Recio-Rodríguez Spain
Yun‐Ju Lai relative to Masoud Rahmati Iran Masoud Rahmati's profile →
Citations per field
00.5×10×15×20×22.5×
Masoud Rahmati · 1×
Citations per year

Countries citing papers authored by Yun‐Ju Lai

Since Specialization
Citations

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

Fields of papers citing papers by Yun‐Ju Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yun‐Ju Lai. 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 Yun‐Ju Lai. The network helps show where Yun‐Ju Lai may publish in the future.

Co-authorship network of co-authors of Yun‐Ju Lai

This figure shows the co-authorship network connecting the top 25 collaborators of Yun‐Ju Lai. A scholar is included among the top collaborators of Yun‐Ju Lai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yun‐Ju Lai. Yun‐Ju Lai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 1
4 17
5 4
6 6
7 19
8 19
9 0
10 5
11 1
12 37
13 21
14 6
15 36
16 31
17 16
18 48
19 5
20 11

About Yun‐Ju Lai

Yun‐Ju Lai is a scholar working on Obstetrics and Gynecology, Pediatrics, Perinatology and Child Health and Endocrinology, Diabetes and Metabolism, having authored 95 papers that have together received 1.5k indexed citations. Recurring topics across this work include Pregnancy and preeclampsia studies (11 papers), Obesity, Physical Activity, Diet (9 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (9 papers). The work is most often cited by research in Ophthalmology (156 citations), Neurology (135 citations) and Obstetrics and Gynecology (117 citations). Yun‐Ju Lai has collaborated with scholars based in Taiwan, United States and Australia. Frequent co-authors include Yung‐Feng Yen, Po‐Wen Ku, Hsiao‐Yun Hu, Yu‐Yen Chen, Dachen Chu, Hong‐Ren Yu, Li‐Tung Huang, Pesus Chou, You‐Lin Tain and Te‐Yao Hsu. Their work appears in journals such as PLoS ONE, Scientific Reports and International Journal of Molecular Sciences.

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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