X. Kui

482 total citations
4 papers, 7 citations indexed

About

X. Kui is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, X. Kui has authored 4 papers receiving a total of 7 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 2 papers in Radiology, Nuclear Medicine and Imaging and 1 paper in Molecular Biology. Recurrent topics in X. Kui's work include Radiomics and Machine Learning in Medical Imaging (2 papers), Medical Imaging and Analysis (1 paper) and Connective Tissue Growth Factor Research (1 paper). X. Kui is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (2 papers), Medical Imaging and Analysis (1 paper) and Connective Tissue Growth Factor Research (1 paper). X. Kui collaborates with scholars based in China. X. Kui's co-authors include Lei Yang, Fang Wang, Minzhi Chen, Ying Liu, Haiying Yu, Bo Ma, Bo He, Jau‐Shyong Hong, Shouzheng Jiang and Man Li and has published in prestigious journals such as Scientific Reports and Mechanisms of Ageing and Development.

In The Last Decade

X. Kui

4 papers receiving 7 citations

Peers

X. Kui

AI

EEE

MSOR

MB

PHARM

D. H. Wei China

Vaibhav Godase India

Z. Chai China

X. Liang China

X. Yuan China

M. Wang China

Jorge Fauste Spain

D. A. Millar United Kingdom

A. Mhaske India

Christian Hopps

D. H. Wei China

X. Kui

3 ×0.8

AI

5 ×1.7

EEE

2 ×1.0

MSOR

0 ×0.0

MB

0 ×0.0

PHARM

Citations per year, relative to X. Kui X. Kui (= 1×) peers D. H. Wei

Countries citing papers authored by X. Kui

Since Specialization

Citations

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

Fields of papers citing papers by X. Kui

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of X. Kui

This figure shows the co-authorship network connecting the top 25 collaborators of X. Kui. A scholar is included among the top collaborators of X. Kui 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 X. Kui. X. Kui 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:

4 of 4 papers shown

1.

Huang, Xiaoli, et al.. (2025). Cyr61 promotes D-gal-induced aging C2C12 cell fibrosis by modulating Wnt/β-catenin signaling pathways. Mechanisms of Ageing and Development. 225. 112067–112067. 1 indexed citations

2.

Wang, Fang, Jiaxin Chen, Ying Liu, et al.. (2024). Deep learning-based segmentation and quantitative analysis of lumbar paraspinal muscles and fat infiltration in multicenter T2-weighted MRI data. 2. 100020–100020. 2 indexed citations

3.

Ning, Tao, X. Kui, & Bo Ma. (2024). Deep Learning-Based Survival Prediction for Breast Cancer Using Multi-Modal Data. 67–70. 1 indexed citations

4.

Yu, Haiying, Shouzheng Jiang, Minzhi Chen, et al.. (2024). Machine learning models for daily net radiation prediction across different climatic zones of China. Scientific Reports. 14(1). 20454–20454. 3 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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