Caiting Chu

486 total citations
22 papers, 321 citations indexed

About

Caiting Chu is a scholar working on Radiology, Nuclear Medicine and Imaging, Obstetrics and Gynecology and Reproductive Medicine. According to data from OpenAlex, Caiting Chu has authored 22 papers receiving a total of 321 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Obstetrics and Gynecology and 6 papers in Reproductive Medicine. Recurrent topics in Caiting Chu's work include Ovarian cancer diagnosis and treatment (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and MRI in cancer diagnosis (5 papers). Caiting Chu is often cited by papers focused on Ovarian cancer diagnosis and treatment (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and MRI in cancer diagnosis (5 papers). Caiting Chu collaborates with scholars based in China and Japan. Caiting Chu's co-authors include Wenhua Li, Yanfen Cui, Xiangru Wu, Gang Ren, Ping Zhang, Tingting Wang, Tingting Wang, Shuhui Zhao, Dengbin Wang and Bing Yin and has published in prestigious journals such as PLoS ONE, Scientific Reports and Pediatric Research.

In The Last Decade

Caiting Chu

18 papers receiving 307 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Caiting Chu China 11 143 140 134 69 35 22 321
Olivera Nikolić Serbia 7 151 1.1× 73 0.5× 96 0.7× 72 1.0× 9 0.3× 33 284
Priyadarshani R. Bhosale United States 10 154 1.1× 45 0.3× 128 1.0× 107 1.6× 15 0.4× 13 267
Canan Çimşit Türkiye 10 32 0.2× 56 0.4× 79 0.6× 78 1.1× 28 0.8× 31 286
Matthias Matzko Germany 9 130 0.9× 75 0.5× 156 1.2× 122 1.8× 3 0.1× 19 360
N Howden United States 7 70 0.5× 49 0.3× 92 0.7× 207 3.0× 21 0.6× 8 371
Ann E. Podrasky United States 9 86 0.6× 32 0.2× 86 0.6× 66 1.0× 27 0.8× 12 282
Abdelbasset A. Badawy Egypt 8 29 0.2× 24 0.2× 76 0.6× 84 1.2× 112 3.2× 17 324
A Denis United States 5 171 1.2× 9 0.1× 30 0.2× 129 1.9× 38 1.1× 9 315
I Kimura Japan 10 538 3.8× 76 0.5× 427 3.2× 197 2.9× 39 1.1× 12 716
Laurien Goedemans Netherlands 10 41 0.3× 114 0.8× 105 0.8× 156 2.3× 8 0.2× 21 482

Countries citing papers authored by Caiting Chu

Since Specialization
Citations

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

Fields of papers citing papers by Caiting Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Caiting Chu

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

All Works

20 of 20 papers shown
1.
2.
Chu, Caiting, Lijun Wang, Shanshan Xu, et al.. (2023). Multidimensional analysis using low-dose computed tomography to evaluate the severity of Mycoplasma pneumoniae pneumonia in children. Quantitative Imaging in Medicine and Surgery. 13(3). 1874–1886. 3 indexed citations
3.
Wang, Lijun, Shanshan Xu, Huajun Li, et al.. (2022). The role of flexible bronchoscopy in children with Mycoplasma pneumoniae pneumonia. Pediatric Research. 93(1). 198–206. 18 indexed citations
4.
Chu, Caiting, Ming Liu, Yuzhen Zhang, et al.. (2022). MRI-Based Radiomics Analysis for Intraoperative Risk Assessment in Gravid Patients at High Risk with Placenta Accreta Spectrum. Diagnostics. 12(2). 485–485. 9 indexed citations
5.
Chu, Caiting, Lei Xu, & Chengjin Gao. (2022). Chest imaging characteristics of mycoplasma pneumoniae pneumonia in children. 9(2). 58–61. 2 indexed citations
6.
Chu, Caiting, et al.. (2021). Quantifying magnetic resonance imaging features to classify placenta accreta spectrum (PAS) in high-risk gravid patients. Clinical Imaging. 80. 50–57. 8 indexed citations
7.
Wang, Tingting, Jing Gong, Caiting Chu, et al.. (2021). A combined radiomics and clinical variables model for prediction of malignancy in T2 hyperintense uterine mesenchymal tumors on MRI. European Radiology. 31(8). 6125–6135. 22 indexed citations
8.
Zhang, Liya, Lijun Wang, Shanshan Xu, et al.. (2020). Low-Dose Corticosteroid Treatment in Children With Mycoplasma pneumoniae Pneumonia: A Retrospective Cohort Study. Frontiers in Pediatrics. 8. 566371–566371. 6 indexed citations
9.
Zhao, Shuhui, Fan Sun, Lei Bao, et al.. (2020). Pure dysgerminoma of the ovary: CT and MRI features with pathological correlation in 13 tumors. Journal of Ovarian Research. 13(1). 71–71. 17 indexed citations
10.
Li, Wenhua, Yongjie Wang, Xiangru Wu, & Caiting Chu. (2019). Epithelioid angiomyolipoma of the uterus: a case report and review of literature. Biomedical Research-tokyo. 30(6). 1–3. 1 indexed citations
11.
Chu, Caiting, Shuhui Zhao, Ming Ding, et al.. (2019). Combining Clinical Characteristics and Specific Magnetic Resonance Imaging Features to Predict Placenta Accreta. Journal of Computer Assisted Tomography. 43(5). 775–779. 15 indexed citations
12.
Fan, Hua, Tingting Wang, Gang Ren, et al.. (2018). Characterization of tubo-ovarian abscess mimicking adnexal masses: Comparison between contrast-enhanced CT, 18F–FDG PET/CT and MRI. Taiwanese Journal of Obstetrics and Gynecology. 57(1). 40–46. 7 indexed citations
13.
Fan, Hua, et al.. (2017). The Correlation of Pirani and Dimeglio Scoring Systems for Ponseti Management at Different Levels of Deformity Severity. Scientific Reports. 7(1). 14578–14578. 20 indexed citations
14.
Wang, Tingting, Wenhua Li, Xiangru Wu, et al.. (2016). Tubo-Ovarian Abscess (with/without Pseudotumor Area) Mimicking Ovarian Malignancy: Role of Diffusion-Weighted MR Imaging with Apparent Diffusion Coefficient Values. PLoS ONE. 11(2). e0149318–e0149318. 15 indexed citations
15.
16.
Wang, Tingting, Wenhua Li, Xiangru Wu, et al.. (2014). Nasal chondromesenchymal hamartoma in young children: CT and MRI findings and review of the literature. World Journal of Surgical Oncology. 12(1). 257–257. 20 indexed citations
17.
Wang, Tingting, Xiangru Wu, Yanfen Cui, et al.. (2014). Role of apparent diffusion coefficients with diffusion-weighted magnetic resonance imaging in differentiating between benign and malignant bone tumors. World Journal of Surgical Oncology. 12(1). 365–365. 26 indexed citations
18.
Chu, Caiting. (2012). Clinical application and research of diffusion weighted MR imaging in complex ovarian tumors. 3 indexed citations
19.
Cui, Yanfen, et al.. (2012). Diagnostic accuracy of diffusion-weighted imaging with conventional MR imaging for differentiating complex solid and cystic ovarian tumors at 1.5T. World Journal of Surgical Oncology. 10(1). 237–237. 48 indexed citations
20.

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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