Juan Zhao

4.3k total citations · 3 hit papers
43 papers, 2.4k citations indexed

About

Juan Zhao is a scholar working on Molecular Biology, Artificial Intelligence and Information Systems. According to data from OpenAlex, Juan Zhao has authored 43 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 12 papers in Artificial Intelligence and 7 papers in Information Systems. Recurrent topics in Juan Zhao's work include Blockchain Technology Applications and Security (7 papers), Machine Learning in Healthcare (6 papers) and Spectroscopy and Chemometric Analyses (6 papers). Juan Zhao is often cited by papers focused on Blockchain Technology Applications and Security (7 papers), Machine Learning in Healthcare (6 papers) and Spectroscopy and Chemometric Analyses (6 papers). Juan Zhao collaborates with scholars based in United States, China and United Kingdom. Juan Zhao's co-authors include Wei‐Qi Wei, Sachin Shetty, Xueping Liang, Danyi Li, Kevin B. Johnson, Karl E. Misulis, Jane Snowdon, Mark E. Frisse, Dilhan Weeraratne and Kyu Rhee and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Applied Physics.

In The Last Decade

Juan Zhao

43 papers receiving 2.3k citations

Hit Papers

Precision Medicine, AI, and the Future of Personalized He... 2017 2026 2020 2023 2020 2017 2019 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Juan Zhao United States 15 586 564 446 368 314 43 2.4k
Faraz S. Ahmad United States 26 648 1.1× 260 0.5× 674 1.5× 164 0.4× 224 0.7× 120 2.3k
Samer Ellahham United Arab Emirates 28 999 1.7× 313 0.6× 389 0.9× 159 0.4× 184 0.6× 70 3.0k
Feipei Lai Taiwan 30 542 0.9× 774 1.4× 720 1.6× 87 0.2× 240 0.8× 293 3.5k
Truyen Tran Australia 24 420 0.7× 1.2k 2.2× 278 0.6× 175 0.5× 246 0.8× 101 3.3k
Amar K. Das United States 25 307 0.5× 968 1.7× 298 0.7× 132 0.4× 662 2.1× 123 2.8k
Shuang Wang China 32 260 0.4× 1.2k 2.2× 116 0.3× 116 0.3× 564 1.8× 210 3.1k
José Luís Oliveira Portugal 29 278 0.5× 966 1.7× 276 0.6× 52 0.1× 1.2k 3.8× 263 3.2k
Prakash M. Nadkarni United States 22 204 0.3× 931 1.7× 105 0.2× 151 0.4× 640 2.0× 83 2.3k
Huilong Duan China 29 301 0.5× 980 1.7× 109 0.2× 89 0.2× 587 1.9× 219 3.0k
You Chen United States 24 191 0.3× 614 1.1× 255 0.6× 101 0.3× 174 0.6× 140 2.1k

Countries citing papers authored by Juan Zhao

Since Specialization
Citations

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

Fields of papers citing papers by Juan Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juan Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Juan Zhao. A scholar is included among the top collaborators of Juan Zhao 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 Juan Zhao. Juan Zhao 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
1.
Yan, Hao, et al.. (2025). Efficient edge-based data integrity auditing in cloud storage. Future Generation Computer Systems. 172. 107899–107899. 1 indexed citations
2.
Hall, Jennifer L., et al.. (2024). Empowering Research With the American Heart Association Get With The Guidelines Registries Through Integration of a Database and Research Tools. Circulation Cardiovascular Quality and Outcomes. 17(9). e010967–e010967. 2 indexed citations
3.
Liang, Xueping, Juan Zhao, Yan Chen, Eranga Bandara, & Sachin Shetty. (2023). Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study. Journal of Medical Internet Research. 25. e46547–e46547. 10 indexed citations
4.
Stevens, Laura, Juan Zhao, Chuan Hong, et al.. (2023). Facilitating Harmonization of Variables in Framingham, MESA, ARIC, and REGARDS Studies Through a Metadata Repository. Circulation Cardiovascular Quality and Outcomes. 16(11). e009938–e009938. 1 indexed citations
5.
Zhao, Juan, Wei‐Qi Wei, Garick D. Hill, et al.. (2023). Machine Learning to Predict Interstage Mortality Following Single Ventricle Palliation: A NPC-QIC Database Analysis. Pediatric Cardiology. 44(6). 1242–1250. 4 indexed citations
6.
Li, Yanan, Xupeng Wang, Ran Sun, et al.. (2023). Effect of pre-infusion of hypertonic saline on postoperative delirium in geriatric patients undergoing shoulder arthroscopy: a randomized controlled trial. BMC Anesthesiology. 23(1). 405–405. 1 indexed citations
7.
Wu, Patrick, et al.. (2023). Evaluating and mitigating bias in machine learning models for cardiovascular disease prediction. Journal of Biomedical Informatics. 138. 104294–104294. 32 indexed citations
8.
Boakye, Ellen, Juan Zhao, Pamela Ouyang, et al.. (2023). Reproductive Experiences and Cardiovascular Disease Care in Pregnancy-Capable and Postmenopausal Individuals: Insights From the American Heart Association Research Goes Red Registry. Current Problems in Cardiology. 48(10). 101853–101853. 2 indexed citations
9.
Zhao, Juan, V. Eric Kerchberger, Joshua Smith, et al.. (2021). ConceptWAS: A high-throughput method for early identification of COVID-19 presenting symptoms and characteristics from clinical notes. Journal of Biomedical Informatics. 117. 103748–103748. 11 indexed citations
10.
Zhao, Juan, QiPing Feng, Patrick Wu, et al.. (2019). Using topic modeling via non-negative matrix factorization to identify relationships between genetic variants and disease phenotypes: A case study of Lipoprotein(a) (LPA). PLoS ONE. 14(2). e0212112–e0212112. 26 indexed citations
11.
Wu, Patrick, Aliya Gifford, Xiangrui Meng, et al.. (2019). Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation. JMIR Medical Informatics. 7(4). e14325–e14325. 255 indexed citations breakdown →
12.
Zhao, Juan, Yanhong Zhou, Nian Xiong, et al.. (2019). Presence of recombination hotspots throughout SLC6A3. PLoS ONE. 14(6). e0218129–e0218129. 4 indexed citations
13.
Zhao, Juan, QiPing Feng, Patrick Wu, et al.. (2019). Learning from Longitudinal Data in Electronic Health Record and Genetic Data to Improve Cardiovascular Event Prediction. Scientific Reports. 9(1). 717–717. 123 indexed citations
14.
Wang, Yanling, Yongxin Yan, Jing Chen, et al.. (2018). The role of E2F1-topoIIβ signaling in regulation of cell cycle exit and neuronal differentiation of human SH-SY5Y cells. Differentiation. 104. 1–12. 8 indexed citations
15.
Liang, Xueping, Juan Zhao, Sachin Shetty, & Danyi Li. (2017). Towards data assurance and resilience in IoT using blockchain. 261–266. 138 indexed citations
16.
Liang, Xueping, Juan Zhao, Sachin Shetty, Jihong Liu, & Danyi Li. (2017). Integrating blockchain for data sharing and collaboration in mobile healthcare applications. 1–5. 439 indexed citations breakdown →
19.
Zhang, Xiaohua, Hai‐Long Wu, Jianyao Wang, et al.. (2012). Fast HPLC-DAD quantification of nine polyphenols in honey by using second-order calibration method based on trilinear decomposition algorithm. Food Chemistry. 138(1). 62–69. 50 indexed citations

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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