Xiaoting Tao

802 citations
21 papers · 288 · h-index 11

Impact in

Papers in

Xiaoting Tao

19 papers receiving 287 citations

Peers

Xiaoting Tao
Comparison fields: 5 of 55
  • Geriatrics and Gerontology 33
  • Cancer Research 59
  • Pulmonary and Respiratory Medicine 93
  • Molecular Biology 101
  • Microbiology 1
Replace Zhaoya Gao with:
Zhaoya Gao China
Yingjian Song China
Matthias PA Ebert Germany
Xuening Zhang China
Nathalie Timmerman Netherlands
Catriona Ling Canada
Richard A. Veldhoen Canada
Amanda M. Dann United States
Enrico Caliman Italy
Xiaoting Tao relative to Zhaoya Gao China Zhaoya Gao's profile →
Citations per field
00.5×8.3×
Zhaoya Gao · 1×
Citations per year

Countries citing papers authored by Xiaoting Tao

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoting Tao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaoting Tao, 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 Xiaoting Tao Line = papers co-authored together Xiaoting Tao links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201954
2 201835
3 201831
4 201926
5 202122
6 201921
7 201918
8 201715
9 202014
10 202014
11 202212
12 20197
13 20247
14 20234
15 20233
16 20222
17 20211
18 20231
19 20221
20 20250

About Xiaoting Tao

Xiaoting Tao is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology, Biomedical Engineering, Infectious Diseases and Surgery, having authored 21 papers that have together received 288 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (3 papers), Phonocardiography and Auscultation Techniques (3 papers), Extracellular vesicles in disease (2 papers), Non-Invasive Vital Sign Monitoring (2 papers), Medical Imaging and Pathology Studies (1 paper), SARS-CoV-2 and COVID-19 Research (1 paper), SARS-CoV-2 detection and testing (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Geriatrics and Gerontology (33 citations), Cancer Research (59 citations), Pulmonary and Respiratory Medicine (93 citations), Molecular Biology (101 citations) and Microbiology (1 citation). Xiaoting Tao has collaborated with scholars based in China, Netherlands and United States. Frequent co-authors include Yihua Sun, Chongze Yuan, Muyu Kuang, Yunjian Pan, Difan Zheng, Hong Hu, Yue Zhao, Haiquan Chen, Jiaqing Xiang and Haiquan Chen. Their work appears in journals such as Genome biology, Translational Lung Cancer Research, PLoS ONE, Journal of Surgical Oncology and IEEE Journal of Biomedical and Health Informatics.

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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