Bao H.

519 total citations
13 papers, 363 citations indexed

About

Bao H. is a scholar working on Surgery, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Bao H. has authored 13 papers receiving a total of 363 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Surgery, 6 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Artificial Intelligence. Recurrent topics in Bao H.'s work include Radiomics and Machine Learning in Medical Imaging (4 papers), Medical Imaging Techniques and Applications (2 papers) and Biomedical Text Mining and Ontologies (2 papers). Bao H. is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), Medical Imaging Techniques and Applications (2 papers) and Biomedical Text Mining and Ontologies (2 papers). Bao H. collaborates with scholars based in United States. Bao H.'s co-authors include Constance R. Chu, Ashley Williams, Christopher F. Beaulieu, Curtis P. Langlotz, Sandip Biswal, Robin V. West, Freddie H. Fu, Yongxian Qian, Andrew S. Wu and Daniel L. Rubin and has published in prestigious journals such as Spine, The American Journal of Sports Medicine and Journal of Orthopaedic Research®.

In The Last Decade

Bao H.

12 papers receiving 356 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bao H. United States 10 174 151 122 62 57 13 363
Yannik Leonhardt Germany 10 77 0.4× 151 1.0× 88 0.7× 33 0.5× 27 0.5× 23 289
Mateusz C. Florkow Netherlands 9 106 0.6× 239 1.6× 132 1.1× 39 0.6× 27 0.5× 12 427
David W. Piraino United States 10 338 1.9× 132 0.9× 122 1.0× 186 3.0× 33 0.6× 26 577
Mazen Soufi Japan 10 61 0.4× 172 1.1× 86 0.7× 10 0.2× 53 0.9× 27 292
Huaiyu Wu China 10 71 0.4× 101 0.7× 41 0.3× 14 0.2× 60 1.1× 32 252
Silvana Sdao Italy 9 120 0.7× 136 0.9× 67 0.5× 12 0.2× 20 0.4× 15 280
Faraz Farhadi United States 13 54 0.3× 321 2.1× 219 1.8× 10 0.2× 46 0.8× 36 481
Brooke Crawford United States 10 112 0.6× 41 0.3× 86 0.7× 20 0.3× 21 0.4× 34 314
Moozhan Nikpanah United States 12 33 0.2× 217 1.4× 115 0.9× 33 0.5× 28 0.5× 31 350
Mischa Woisetschläger Sweden 10 45 0.3× 289 1.9× 260 2.1× 9 0.1× 15 0.3× 31 422

Countries citing papers authored by Bao H.

Since Specialization
Citations

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

Fields of papers citing papers by Bao H.

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bao H.

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

All Works

13 of 13 papers shown
1.
2.
Beaulieu, Christopher F., et al.. (2024). Deep Learning for Automated Classification of Hip Hardware on Radiographs. Journal of Imaging Informatics in Medicine. 38(2). 988–996. 1 indexed citations
3.
H., Bao, Albert Hsiao, A.M. Lutz, et al.. (2022). Automating Scoliosis Measurements in Radiographic Studies with Machine Learning: Comparing Artificial Intelligence and Clinical Reports. Journal of Digital Imaging. 35(3). 524–533. 18 indexed citations
4.
H., Bao, et al.. (2020). Artificial Intelligence and Machine Learning Applications in Musculoskeletal Imaging. 2. 285–297. 3 indexed citations
5.
Shpanskaya, Katie, Michelle Han, Edward H. Lee, et al.. (2019). Deep Learning for Automated Classification of Inferior Vena Cava Filter Types on Radiographs. Journal of Vascular and Interventional Radiology. 31(1). 66–73. 10 indexed citations
6.
Williams, Ashley, et al.. (2018). MRI UTE‐T2* shows high incidence of cartilage subsurface matrix changes 2 years after ACL reconstruction. Journal of Orthopaedic Research®. 37(2). 370–377. 29 indexed citations
7.
H., Bao, Curtis P. Langlotz, & Christopher F. Beaulieu. (2017). Bone Tumor Diagnosis Using a Naïve Bayesian Model of Demographic and Radiographic Features. Journal of Digital Imaging. 30(5). 640–647. 57 indexed citations
8.
Gutiérrez, Luis B., Bao H., Garry E. Gold, et al.. (2014). MR Imaging Near Metallic Implants Using MAVRIC SL. Academic Radiology. 22(3). 370–379. 37 indexed citations
9.
Chu, Constance R., Ashley Williams, Robin V. West, et al.. (2014). Quantitative Magnetic Resonance Imaging UTE-T2* Mapping of Cartilage and Meniscus Healing After Anatomic Anterior Cruciate Ligament Reconstruction. The American Journal of Sports Medicine. 42(8). 1847–1856. 109 indexed citations
10.
H., Bao, Andrew S. Wu, Joan E. Maley, & Sandip Biswal. (2012). Automatic Retrieval of Bone Fracture Knowledge Using Natural Language Processing. Journal of Digital Imaging. 26(4). 709–713. 25 indexed citations
11.
H., Bao, C Marí, Jeffrey R. Tseng, et al.. (2011). Pattern of 18F-FDG Uptake in the Spinal Cord in Patients With Non-Central Nervous System Malignancy. Spine. 36(21). E1395–E1401. 29 indexed citations
12.
H., Bao, Andrew S. Wu, Sandip Biswal, Aya Kamaya, & Daniel L. Rubin. (2010). Informatics in Radiology: RADTF: A Semantic Search–enabled, Natural Language Processor–generated Radiology Teaching File. Radiographics. 30(7). 2039–2048. 32 indexed citations
13.
Wu, Andrew S., Bao H., Jinsuh Kim, & Daniel L. Rubin. (2009). Evaluation of Negation and Uncertainty Detection and its Impact on Precision and Recall in Search. Journal of Digital Imaging. 24(2). 234–242. 13 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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