Tianle Han

959 total citations · 1 hit paper
6 papers, 441 citations indexed

About

Tianle Han is a scholar working on Health Informatics, Artificial Intelligence and Neurology. According to data from OpenAlex, Tianle Han has authored 6 papers receiving a total of 441 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Health Informatics, 2 papers in Artificial Intelligence and 2 papers in Neurology. Recurrent topics in Tianle Han's work include Machine Learning in Healthcare (2 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Transcranial Magnetic Stimulation Studies (2 papers). Tianle Han is often cited by papers focused on Machine Learning in Healthcare (2 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Transcranial Magnetic Stimulation Studies (2 papers). Tianle Han collaborates with scholars based in China and United States. Tianle Han's co-authors include Qiang Ning, Zhengliang Liu, Xiang Li, Bao Ge, Tianming Liu, Yiheng Liu, Dajiang Zhu, Mengshen He, Lin Zhao and Jiaming Tian and has published in prestigious journals such as SHILAP Revista de lepidopterología, BMJ Open and Trials.

In The Last Decade

Tianle Han

6 papers receiving 421 citations

Hit Papers

Summary of ChatGPT-Related research and perspective towar... 2023 2026 2024 2025 2023 100 200 300 400

Peers

Tianle Han
Tianle Han
Citations per year, relative to Tianle Han Tianle Han (= 1×) peers Mengshen He

Countries citing papers authored by Tianle Han

Since Specialization
Citations

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

Fields of papers citing papers by Tianle Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tianle Han

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

All Works

6 of 6 papers shown
3.
Wang, Aiming, et al.. (2023). Weighted IMF-based denoising and multi-scale kurtosis weighted K singular value decomposition dictionary learning model for bearing fault diagnosis. Journal of Vibration and Control. 30(17-18). 4010–4020. 2 indexed citations
4.
Liu, Yiheng, Tianle Han, Yuanyuan Yang, et al.. (2023). Summary of ChatGPT-Related research and perspective towards the future of large language models. SHILAP Revista de lepidopterología. 1(2). 100017–100017. 408 indexed citations breakdown →
5.
Cai, Yanhui, Haiyun Guo, Tianle Han, & Huaning Wang. (2023). Lactate: a prospective target for therapeutic intervention in psychiatric disease. Neural Regeneration Research. 19(7). 1473–1479. 12 indexed citations
6.
Liu, Zhengliang, Mengshen He, Zihao Wu, et al.. (2022). Survey on natural language processing in medical image analysis.. PubMed. 47(8). 981–993. 14 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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