Dandan Tu

620 total citations
6 papers, 163 citations indexed

About

Dandan Tu is a scholar working on Pulmonary and Respiratory Medicine, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Dandan Tu has authored 6 papers receiving a total of 163 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Pulmonary and Respiratory Medicine, 3 papers in Artificial Intelligence and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Dandan Tu's work include Radiomics and Machine Learning in Medical Imaging (2 papers), Advanced Neural Network Applications (1 paper) and Airway Management and Intubation Techniques (1 paper). Dandan Tu is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (2 papers), Advanced Neural Network Applications (1 paper) and Airway Management and Intubation Techniques (1 paper). Dandan Tu collaborates with scholars based in China and United Kingdom. Dandan Tu's co-authors include Xiaowu Liu, Changzheng Zhang, Changde Li, Osamah Alwalid, Xi Long, Jia Liu, Yongchao Xu, Cong Fang, Shi Gong and Lixin Qin and has published in prestigious journals such as Radiology, IEEE Transactions on Medical Imaging and Medical Image Analysis.

In The Last Decade

Dandan Tu

6 papers receiving 163 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dandan Tu China	4	76	59	56	43	23	6	163
Xiaowu Liu China	6	78 1.0×	52 0.9×	58 1.0×	39 0.9×	22 1.0×	8	186
Ivan A. Blokhin Russia	8	165 2.2×	48 0.8×	15 0.3×	42 1.0×	44 1.9×	44	227
Joshua Lampert United States	8	33 0.4×	25 0.4×	16 0.3×	28 0.7×	35 1.5×	32	196
Valeria Chernina Russia	6	136 1.8×	47 0.8×	6 0.1×	39 0.9×	34 1.5×	21	175
Pietro Danna Italy	5	80 1.1×	23 0.4×	13 0.2×	25 0.6×	10 0.4×	7	126
Julie K. Shade United States	11	76 1.0×	38 0.6×	11 0.2×	19 0.4×	12 0.5×	16	419
Sunny Virmani United States	7	172 2.3×	29 0.5×	34 0.6×	22 0.5×	17 0.7×	10	254
Nishanth Arun United States	4	209 2.8×	51 0.9×	11 0.2×	125 2.9×	79 3.4×	7	300
Mwaffaq El-Heis Jordan	8	52 0.7×	62 1.1×	9 0.2×	38 0.9×	6 0.3×	24	239
John Ryu United States	5	111 1.5×	26 0.4×	45 0.8×	52 1.2×	59 2.6×	8	213

Countries citing papers authored by Dandan Tu

Since Specialization

Citations

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

Fields of papers citing papers by Dandan Tu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dandan Tu

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

All Works

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6 of 6 papers shown

1.

Huang, Lei, Xiaocheng Feng, Weitao Ma, et al.. (2024). Learning Fine-Grained Grounded Citations for Attributed Large Language Models. 14095–14113. 1 indexed citations

2.

Li, Xiang, Dandan Tu, Changzheng Zhang, et al.. (2023). Unsupervised Cross-Modality Adaptation via Dual Structural-Oriented Guidance for 3D Medical Image Segmentation. IEEE Transactions on Medical Imaging. 42(6). 1774–1785. 20 indexed citations

3.

Wang, Yimin, Yicong Li, Changzheng Zhang, et al.. (2022). Deep learning for spirometry quality assurance with spirometric indices and curves. Respiratory Research. 23(1). 98–98. 9 indexed citations

4.

Wang, Yimin, Yicong Li, Changzheng Zhang, et al.. (2022). Deep Learning for Automatic Upper Airway Obstruction Detection by Analysis of Flow-Volume Curve. Respiration. 101(9). 841–850. 2 indexed citations

5.

Fang, Cong, Song Bai, Qianlan Chen, et al.. (2021). Deep learning for predicting COVID-19 malignant progression. Medical Image Analysis. 72. 102096–102096. 57 indexed citations

6.

Alwalid, Osamah, Yongchao Xu, Jia Liu, et al.. (2020). Deep Learning for Detecting Cerebral Aneurysms with CT Angiography. Radiology. 298(1). 155–163. 74 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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