Ching‐Long Lai

694 citations
28 papers · 581 · h-index 14

Impact in

Papers in

Ching‐Long Lai

27 papers receiving 563 citations

Peers

Ching‐Long Lai
Comparison fields: 5 of 84
  • Pathology and Forensic Medicine 281
  • Biochemistry 60
  • Pharmacology 35
  • Epidemiology 104
  • Endocrinology, Diabetes and Metabolism 50
Replace Alberto Moreno with:
Alberto Moreno Spain
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Liuyi Hao United States
Agarwal Dp India
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L Mikulíková Czechia
Paul G. Thomes United States
Christina Chui‐Wa Poon Hong Kong
Hyun-Ju Jang South Korea
Xueyu Fan China
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Citations per field
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Citations per year

Countries citing papers authored by Ching‐Long Lai

Since Specialization
Citations

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

Fields of papers citing papers by Ching‐Long Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997109
2 201380
3 201658
4 200346
5 201440
6 200236
7 200025
8 201523
9 201618
10 201817
11 201216
12 202114
13 199613
14
Heavy binge drinking may increase risk of stroke in nonalcoholic hypertensives carrying variant ALDH2*2 gene allele.
201213
15 201013
16 202011
17 20189
18 20168
19 20257
20 20227

About Ching‐Long Lai

Ching‐Long Lai is a scholar working on Pathology and Forensic Medicine, Molecular Biology, Biochemistry, Epidemiology and Pharmacology, having authored 28 papers that have together received 581 indexed citations. Recurring topics across this work include Alcohol Consumption and Health Effects (15 papers), Eicosanoids and Hypertension Pharmacology (5 papers), Liver Disease Diagnosis and Treatment (4 papers), Algal biology and biofuel production (2 papers), Gut microbiota and health (2 papers), Cannabis and Cannabinoid Research (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers) and High Altitude and Hypoxia (1 paper). The work is most often cited by research in Pathology and Forensic Medicine (281 citations), Biochemistry (60 citations), Pharmacology (35 citations), Epidemiology (104 citations) and Endocrinology, Diabetes and Metabolism (50 citations). Ching‐Long Lai has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Shih‐Jiun Yin, Chung‐Tay Yao, Cheng‐Wei Wu, Chu‐Fang Chou, Chien‐Ping Chiang, Gar‐Yang Chau, Giia‐Sheun Peng, Wen‐Chung Huang, Chian‐Jiun Liou and Hui‐Chih Hung. Their work appears in journals such as Alcoholism Clinical and Experimental Research, Chemico-Biological Interactions, Nutrients, Physiologia Plantarum and Pharmacogenetics and Genomics.

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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