Nan Liu

537 papers receiving 10.2k citations

Nan Liu's Hit Papers

Retrieval augmented generation for 10 large language models and its generalizability in assessing medical fitness 2025 · 38 citations
380+4+9Years since publication200400600

Peers

Nan Liu
Comparison fields: 5 of 213
  • Health Informatics 541
  • Statistics, Probability and Uncertainty 524
  • Emergency Medicine 577
  • Health Information Management 277
  • Artificial Intelligence 2.0k
Replace Mourad Ouzzani with:
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Citations per year

Countries citing papers authored by Nan Liu

Since Specialization
Citations

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

Fields of papers citing papers by Nan Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 579 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Risk evaluation approaches in failure mode and effects analysis: A literature review
Hit paper breakdown →
2012684
2
A Blockchain-Based Decentralized Federated Learning Framework with Committee Consensus
Hit paper breakdown →
2020430
3 2012302
4 2011287
5 2023202
6 2010195
7 2015147
8
Ethical and regulatory challenges of large language models in medicine
Hit paper breakdown →
2024140
9 2014128
10 2003123
11 2012105
12 2012104
13 2012104
14 2019102
15 2019100
16 201996
17 201795
18 201490
19 201688
20
Tissue expression of neu differentiation factor/heregulin and its receptor complex in prostate cancer and its biologic effects on prostate cancer cells in vitro.
199788

About Nan Liu

Nan Liu is a scholar working on Artificial Intelligence, Cardiology and Cardiovascular Medicine, Molecular Biology, Pulmonary and Respiratory Medicine and Epidemiology, having authored 579 papers that have together received 10.4k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (25 papers), Machine Learning in Healthcare (25 papers), Emergency and Acute Care Studies (20 papers), Cardiac Arrest and Resuscitation (18 papers), Heart Rate Variability and Autonomic Control (17 papers), Sepsis Diagnosis and Treatment (16 papers), Face and Expression Recognition (15 papers) and Air Quality and Health Impacts (14 papers). The work is most often cited by research in Health Informatics (541 citations), Statistics, Probability and Uncertainty (524 citations), Emergency Medicine (577 citations), Health Information Management (277 citations) and Artificial Intelligence (2.0k citations). Nan Liu has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Long Liu, Hu‐Chen Liu, Marcus Eng Hock Ong, Zhiping Lin, Han Wang, Jidong Kang, Daniel Shu Wei Ting, Andrew Fu Wah Ho, Jiuwen Cao and Zujun Ma. Their work appears in journals such as Scientific Reports, PLoS ONE, Medicine, Journal of Medical Internet Research and BMC Medical Research Methodology.

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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