Shi-ang Qi

558 total citations
11 papers, 351 citations indexed

About

Shi-ang Qi is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Shi-ang Qi has authored 11 papers receiving a total of 351 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 4 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Molecular Biology. Recurrent topics in Shi-ang Qi's work include Machine Learning in Healthcare (2 papers), Topic Modeling (2 papers) and Dementia and Cognitive Impairment Research (2 papers). Shi-ang Qi is often cited by papers focused on Machine Learning in Healthcare (2 papers), Topic Modeling (2 papers) and Dementia and Cognitive Impairment Research (2 papers). Shi-ang Qi collaborates with scholars based in Canada, China and Greece. Shi-ang Qi's co-authors include Jie Chen, Yufeng Li, Xiaoxue Jiang, Oleksandra Savchenko, Wei Zhang, Russell Greiner, Eleni Stroulia, Yongchun Zhou, Qian Wu and Yuanyuan Li and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Shi-ang Qi

11 papers receiving 348 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shi-ang Qi Canada	6	153	75	63	52	37	11	351
Jin hwan Yoon South Korea	8	80 0.5×	27 0.4×	46 0.7×	18 0.3×	15 0.4×	57	335
Veysi Akpolat Türkiye	12	51 0.3×	54 0.7×	50 0.8×	70 1.3×	8 0.2×	36	402
Simona Bondari Romania	8	34 0.2×	41 0.5×	57 0.9×	17 0.3×	14 0.4×	29	279
Zenggan Chen China	11	48 0.3×	46 0.6×	74 1.2×	70 1.3×	9 0.2×	38	398
Guocai Chen China	6	33 0.2×	62 0.8×	13 0.2×	47 0.9×	17 0.5×	21	248
Yannan Cheng China	10	123 0.8×	29 0.4×	145 2.3×	11 0.2×	7 0.2×	25	308
Yingying Bai China	13	35 0.2×	177 2.4×	63 1.0×	7 0.1×	11 0.3×	46	457
Reza Rahmanzadeh Iran	10	38 0.2×	88 1.2×	130 2.1×	17 0.3×	16 0.4×	24	436
Xiao Fan China	11	39 0.3×	65 0.9×	17 0.3×	14 0.3×	7 0.2×	38	330

Countries citing papers authored by Shi-ang Qi

Since Specialization

Citations

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

Fields of papers citing papers by Shi-ang Qi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shi-ang Qi. 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 Shi-ang Qi. The network helps show where Shi-ang Qi may publish in the future.

Co-authorship network of co-authors of Shi-ang Qi

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

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

Qi, Shi-ang, et al.. (2024). SurvivalEVAL: A Comprehensive Open-Source Python Package for Evaluating Individual Survival Distributions. Proceedings of the AAAI Symposium Series. 2(1). 453–457. 3 indexed citations

Kalmady, Sunil V., Shi-ang Qi, Nariman Sepehrvand, et al.. (2024). Predicting Individual Survival Distributions Using ECG: A Deep Learning Approach Utilizing Features Extracted by a Learned Diagnostic Model. Proceedings of the AAAI Symposium Series. 2(1). 475–481. 1 indexed citations

Qi, Shi-ang, Neeraj Kumar, Ruchika Verma, et al.. (2023). Using Bayesian Neural Networks to Select Features and Compute Credible Intervals for Personalized Survival Prediction. IEEE Transactions on Biomedical Engineering. 70(12). 3389–3400. 2 indexed citations

Qi, Shi-ang, et al.. (2023). ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis. 13610–13624. 15 indexed citations

Qi, Shi-ang, et al.. (2023). Exploring Language-Agnostic Speech Representations Using Domain Knowledge for Detecting Alzheimer’s Dementia. Zenodo (CERN European Organization for Nuclear Research). 1–2. 9 indexed citations

Kumar, Neeraj, et al.. (2022). Learning accurate personalized survival models for predicting hospital discharge and mortality of COVID-19 patients. Scientific Reports. 12(1). 4472–4472. 6 indexed citations

Qi, Shi-ang, Neeraj Kumar, Jianyi Xu, et al.. (2022). Personalized breast cancer onset prediction from lifestyle and health history information. PLoS ONE. 17(12). e0279174–e0279174. 5 indexed citations

Qi, Shi-ang, Qian Wu, Wei Zhang, et al.. (2021). High-resolution metabolomic biomarkers for lung cancer diagnosis and prognosis. Scientific Reports. 11(1). 11805–11805. 53 indexed citations

Qi, Shi-ang, et al.. (2021). Learning Language and Acoustic Models for Identifying Alzheimer’s Dementia From Speech. Frontiers in Computer Science. 3. 30 indexed citations

10.

Qi, Shi-ang, et al.. (2018). Design of A Novel Wearable LIPUS Treatment Device for Mental Health Treatment. PubMed. 1. 6052–6055. 2 indexed citations

11.

Jiang, Xiaoxue, Oleksandra Savchenko, Yufeng Li, et al.. (2018). A Review of Low-Intensity Pulsed Ultrasound for Therapeutic Applications. IEEE Transactions on Biomedical Engineering. 66(10). 2704–2718. 225 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.

Explore authors with similar magnitude of impact