Xiaoqian Jiang

14.5k total citations · 2 hit papers
342 papers, 8.4k citations indexed

About

Xiaoqian Jiang is a scholar working on Artificial Intelligence, Molecular Biology and Genetics. According to data from OpenAlex, Xiaoqian Jiang has authored 342 papers receiving a total of 8.4k indexed citations (citations by other indexed papers that have themselves been cited), including 148 papers in Artificial Intelligence, 78 papers in Molecular Biology and 34 papers in Genetics. Recurrent topics in Xiaoqian Jiang's work include Privacy-Preserving Technologies in Data (79 papers), Machine Learning in Healthcare (49 papers) and Cryptography and Data Security (33 papers). Xiaoqian Jiang is often cited by papers focused on Privacy-Preserving Technologies in Data (79 papers), Machine Learning in Healthcare (49 papers) and Cryptography and Data Security (33 papers). Xiaoqian Jiang collaborates with scholars based in United States, China and Canada. Xiaoqian Jiang's co-authors include Fei Wang, Shuang Wang, Joel T. Dudley, Riccardo Miotto, Lucila Ohno‐Machado, Shuang Wang, Miran Kim, Jaideep Vaidya, Jihoon Kim and Hwanjo Yu and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Nature Genetics.

In The Last Decade

Xiaoqian Jiang

309 papers receiving 8.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep learning for healthcare: review, opportunities and challenges

2017 1.7k citations Xiaoqian Jiang et al. profile →
CancerGPT for few shot drug pair synergy prediction using large pretrained language models

2024 59 citations Xiaoqian Jiang, Yejin Kim et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xiaoqian Jiang United States	42	3.7k	1.2k	707	689	642	342	8.4k
Riccardo Bellazzi Italy	46	1.9k 0.5×	2.2k 1.8×	472 0.7×	1.2k 1.8×	604 0.9×	370	8.6k
Jiang Bian United States	40	2.4k 0.6×	977 0.8×	489 0.7×	499 0.7×	751 1.2×	422	7.2k
Yuan Luo United States	57	3.6k 1.0×	3.5k 2.9×	1.2k 1.7×	812 1.2×	327 0.5×	373	12.8k
Fei Wang United States	46	4.0k 1.1×	1.5k 1.3×	1.2k 1.7×	1.3k 1.9×	321 0.5×	297	9.6k
Nan Liu China	48	2.2k 0.6×	1.1k 0.9×	791 1.1×	380 0.6×	365 0.6×	577	10.0k
Yu‐Chuan Li Taiwan	44	1.0k 0.3×	1.7k 1.4×	549 0.8×	1.0k 1.5×	640 1.0×	491	9.9k
Wendy W. Chapman United States	40	3.8k 1.0×	2.9k 2.4×	501 0.7×	908 1.3×	545 0.8×	167	7.4k
Benjamin S. Glicksberg United States	37	1.7k 0.5×	825 0.7×	1.1k 1.5×	614 0.9×	321 0.5×	184	6.7k
Lucila Ohno‐Machado United States	52	4.1k 1.1×	3.5k 2.9×	1.0k 1.4×	1.6k 2.3×	1.5k 2.4×	359	15.0k
Peter Szolovits United States	48	7.0k 1.9×	2.6k 2.1×	926 1.3×	2.1k 3.1×	686 1.1×	177	13.5k

Countries citing papers authored by Xiaoqian Jiang

Since Specialization

Citations

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

Fields of papers citing papers by Xiaoqian Jiang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoqian Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoqian Jiang. A scholar is included among the top collaborators of Xiaoqian Jiang 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 Xiaoqian Jiang. Xiaoqian Jiang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Jiang, Xiaoqian, Yue Hu, Fangsen Cui, et al.. (2025). Physical-guided graph deep learning for composite pipelines structural health monitoring. Structural Health Monitoring.

Jiang, Xiaoqian, Tan Wang, Chen Chen, et al.. (2025). Soft magnetic properties and crystallization behavior of FeSiBPCuNb nanocrystalline alloys. Journal of Materials Science Materials in Electronics. 36(12).

Jiang, Xiaoqian, et al.. (2025). THOR: Secure Transformer Inference with Homomorphic Encryption. 3765–3779.

Dai, Yulin, Brisa S. Fernandes, Kai Zhang, et al.. (2024). Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach. Journal of Alzheimer s Disease. 97(4). 1807–1827. 2 indexed citations

Hong, Na, et al.. (2024). Mapping Study Variables to Common Data Elements Using GPT for Sheets: Towards Standardized Data Collection and Sharing. 320–325.

Li, Rongbin, et al.. (2024). SAFER: sub-hypergraph attention-based neural network for predicting effective responses to dose combinations. BMC Bioinformatics. 25(1). 250–250. 3 indexed citations

Jiang, Xiaoqian, et al.. (2023). A transformer-based deep learning approach for fairly predicting post-liver transplant risk factors. Journal of Biomedical Informatics. 149. 104545–104545. 13 indexed citations

Lai, Kwei-Herng, Daochen Zha, Ruixiang Tang, et al.. (2023). DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research. PubMed. 2023. 5021–5025. 2 indexed citations

Jiang, Xiaoqian, Jin Sun, Jianxin Cao, et al.. (2023). Elsholtzia bodinieri Vaniot ameliorated acute lung injury in mice by regulating pyroptosis, inflammation, oxidative stress and macrophage polarization. Journal of Ethnopharmacology. 307. 116232–116232. 10 indexed citations

10.

Jiang, Xiaoqian, et al.. (2023). Graph Representation Learning For Stroke Recurrence Prediction. 42. 1–5. 1 indexed citations

11.

Li, Rongbin, Yujia Zhou, Laila Rasmy, et al.. (2023). Prediction of Brain Metastases Development in Patients With Lung Cancer by Explainable Artificial Intelligence From Electronic Health Records. JCO Clinical Cancer Informatics. 7(7). e2200141–e2200141. 6 indexed citations

12.

Zou, Na, et al.. (2023). Multi-task learning with dynamic re-weighting to achieve fairness in healthcare predictive modeling. Journal of Biomedical Informatics. 143. 104399–104399. 13 indexed citations

13.

Kuo, Tsung-Ting, Xiaoqian Jiang, Haixu Tang, et al.. (2022). The evolving privacy and security concerns for genomic data analysis and sharing as observed from the iDASH competition. Journal of the American Medical Informatics Association. 29(12). 2182–2190. 13 indexed citations

14.

Xu, Hua, et al.. (2022). Factors Associated With COVID-19 Death in the United States: Cohort Study. JMIR Public Health and Surveillance. 8(5). e29343–e29343. 15 indexed citations

15.

Kim, Yejin, Kai Zhang, Sean I. Savitz, et al.. (2022). Counterfactual analysis of differential comorbidity risk factors in Alzheimer’s disease and related dementias. SHILAP Revista de lepidopterología. 1(3). e0000018–e0000018. 4 indexed citations

16.

Jiang, Xiaoqian, et al.. (2022). Design of dynamic monitoring and anti-theft system for port commodity vehicle’s moving track based on Internet of things. 2. 384–388. 1 indexed citations

17.

Zhang, Kai, et al.. (2022). Scalable Causal Structure Learning: Scoping Review of Traditional and Deep Learning Algorithms and New Opportunities in Biomedicine. JMIR Medical Informatics. 11. e38266–e38266. 7 indexed citations

18.

Kim, Yejin, et al.. (2020). Anticancer drug synergy prediction in understudied tissues using transfer learning. Journal of the American Medical Informatics Association. 28(1). 42–51. 61 indexed citations

19.

Zhu, Cong, et al.. (2020). A lightweight convolutional neural network for assessing an EEG risk marker for sudden unexpected death in epilepsy. BMC Medical Informatics and Decision Making. 20(S12). 329–329. 7 indexed citations

20.

Ohno‐Machado, Lucila, George Hripcsak, Michael E. Matheny, Yuan Wu, & Xiaoqian Jiang. (2016). Calibration of Predictive Models for Clinical Decision Making: Personalizing Prevention, Treatment, and Disease Progression.. AMIA. 1 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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