Xiaobo Lai

1.2k citations
33 papers · 946 · h-index 14

Impact in

Papers in

Xiaobo Lai

28 papers receiving 914 citations

Peers

Xiaobo Lai
Comparison fields: 5 of 90
  • Neurology 327
  • Computer Vision and Pattern Recognition 458
  • Radiology, Nuclear Medicine and Imaging 281
  • Control and Systems Engineering 252
  • Artificial Intelligence 189
Replace Pilar Sobrevilla with:
Pilar Sobrevilla Spain
Jun Jiang China
Toufique Ahmed Soomro Pakistan
T. A. Joyce Switzerland
Chun-Mei Feng China
Yuqian Zhao China
Guanghui Yue China
Shanlin Sun China
Zekuan Yu China
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Citations per field
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Citations per year

Countries citing papers authored by Xiaobo Lai

Since Specialization
Citations

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

Fields of papers citing papers by Xiaobo Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaobo Lai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiaobo Lai Line = papers co-authored together Xiaobo Lai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012213
2 2022103
3 2021100
4 201392
5 202085
6 202179
7 202071
8 202127
9 202122
10 202021
11 202217
12 202017
13 201116
14 201114
15 202112
16 202211
17 202310
18 20229
19 20214
20 20094

About Xiaobo Lai

Xiaobo Lai is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Neurology, Control and Systems Engineering and Pulmonary and Respiratory Medicine, having authored 33 papers that have together received 946 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (12 papers), Advanced Neural Network Applications (10 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), Medical Image Segmentation Techniques (5 papers), AI in cancer detection (3 papers), Robotic Mechanisms and Dynamics (3 papers), Retinal Imaging and Analysis (3 papers) and Glioma Diagnosis and Treatment (3 papers). The work is most often cited by research in Neurology (327 citations), Computer Vision and Pattern Recognition (458 citations), Radiology, Nuclear Medicine and Imaging (281 citations), Control and Systems Engineering (252 citations) and Artificial Intelligence (189 citations). Xiaobo Lai has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Huashan Liu, Wenxiang Wu, Xiaomei Xu, Guang Yang, W. Yang, Ying Fang, Yongkai Liu, Shiqiang Zhu, Wuneng Zhou and He Huang. Their work appears in journals such as International Journal of Imaging Systems and Technology, Computational Intelligence and Neuroscience, Frontiers in Neuroscience, Frontiers in Oncology and Displays.

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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