B. Zhao
About
B. Zhao is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Hepatology.
According to data from OpenAlex, B. Zhao has authored 20 papers receiving a total of 673 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Pulmonary and Respiratory Medicine and 3 papers in Hepatology. Recurrent topics in B. Zhao's work include Radiomics and Machine Learning in Medical Imaging (13 papers), Lung Cancer Diagnosis and Treatment (8 papers) and Lung Cancer Treatments and Mutations (5 papers). B. Zhao is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (13 papers), Lung Cancer Diagnosis and Treatment (8 papers) and Lung Cancer Treatments and Mutations (5 papers). B. Zhao collaborates with scholars based in United States, China and Austria. B. Zhao's co-authors include Anthony P. Reeves, David F. Yankelevitz, William J. Kostis, Claudia I. Henschke, Lawrence H. Schwartz, Nicholas Petrick, P. David Mozley, Andrew J. Buckler, Claus Bendtsen and Vesselin Z. Miloushev and has published in prestigious journals such as Journal of Clinical Oncology, Radiology and Annals of Oncology.
In The Last Decade
B. Zhao
18 papers receiving 657 citations
Peers
B. Zhao
Vincent Bourbonne France
Naira Muradyan United States
Qingtao Qiu China
Martijn P. A. Starmans Netherlands
Virginie Frings Netherlands
Paul Blanc‐Durand France
Khaled Bousabarah United States
Rebecca Rakow‐Penner United States
Aida Kiviniemi Finland
Lars Bornemann Germany
Citations per year, relative to B. Zhao B. Zhao (= 1×)
peers
Vincent Bourbonne
Countries citing papers authored by B. Zhao
Since
Specialization
Citations
This map shows the geographic impact of B. Zhao'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 B. Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites B. Zhao more than expected).
Fields of papers citing papers by B. Zhao
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by B. Zhao. 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 B. Zhao. The network helps show where B. Zhao may publish in the future.
Co-authorship network of co-authors of B. Zhao
This figure shows the co-authorship network connecting the top 25 collaborators of B. Zhao. A scholar is included among the top collaborators of B. Zhao 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 B. Zhao. B. Zhao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Ibrahim, Abdalla, Ramesh Paudyal, Akash Shah, et al.. (2025). Impact of artificial intelligence-based and traditional image preprocessing and resampling on MRI-based radiomics for classification of papillary thyroid carcinoma. PubMed. 2(1). ubaf006–ubaf006.
2.
Zhao, B., et al.. (2025). Observation of bronchial anatomy and variation of the middle lobe of the right lung based on three-dimensional reconstruction of lung CT. Journal of Cardiothoracic Surgery. 20(1). 172–172.
3.
Wang, Yunmei, Guangxi Wang, Xiang Wang, et al.. (2024). Analysis of TLR2 in Primary Endocrine Resistant of Breast Cancer. Frontiers in Bioscience-Landmark. 29(2). 81–81.
4.
Schöffski, Patrick, Patricia LoRusso, Nobuyuki Yamamoto, et al.. (2024). 56O A phase Ia/Ib study of the MDM2-p53 antagonist brigimadlin (BI 907828): Safety and efficacy in patients with dedifferentiated liposarcoma. ESMO Open. 9. 102446–102446.
5.
Goetz, Teddy G., Nandini Nair, Stephanie Shiau, et al.. (2021). In premenopausal women with idiopathic osteoporosis, lower bone formation rate is associated with higher body fat and higher IGF-1. Osteoporosis International. 33(3). 659–672.
6.
Dercle, Laurent, Matthew Fronheiser, Lin Lü, et al.. (2019). Radiomic signatures for identification of tumors sensitive to nivolumab or docetaxel in squamous non-small cell lung cancer (sqNSCLC). Annals of Oncology. 30. v773–v773.
7.
Zhao, B., et al.. (2017). [Clinical significance of low-dose CT performed for three consecutive years in diagnosis of lung nodules in coal mine workers with 20 working years].. PubMed. 35(9). 679–682.
8.
Filippi, Christopher G., Alexander M. El‐Ali, Vesselin Z. Miloushev, et al.. (2014). Computer-Assisted Volumetric Measurement of Core Infarct Volume in Pediatric Patients: Feasibility for Clinical Use and Development of Quantitative Metrics for Outcome Prediction. American Journal of Neuroradiology. 36(4). 789–794.
9.
Brown, Karen T., Mithat Gönen, Richard Kinh Gian, et al.. (2014). Randomized phase II study of hepatic arterial embolization of hepatocellular carcinoma (HCC) with micospheres alone (bead block (BB)) versus doxorubicin loaded microspheres (LC bead (LCB)). Journal of Vascular and Interventional Radiology. 25(3). S24–S24.
10.
Chow, Daniel, Jing Qi, Xia Guo, et al.. (2013). Semiautomated Volumetric Measurement on Postcontrast MR Imaging for Analysis of Recurrent and Residual Disease in Glioblastoma Multiforme. American Journal of Neuroradiology. 35(3). 498–503.
11.
Mozley, P. David, Lawrence H. Schwartz, Claus Bendtsen, et al.. (2010). Change in lung tumor volume as a biomarker of treatment response: a critical review of the evidence. Annals of Oncology. 21(9). 1751–1755.
12.
Buckler, Andrew J., Lawrence H. Schwartz, Nicholas Petrick, et al.. (2010). Data sets for the qualification of volumetric CT as a quantitative imaging biomarker in lung cancer. Optics Express. 18(14). 15267–15267.
13.
Armato, Samuel G., Geoffrey McLennan, Charles R. Meyer, et al.. (2010). WE-B-201B-02: The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Public Database of CT Scans for Lung Nodule Analysis. Medical Physics. 37(6Part6). 3416–3417.
14.
James, Leonard P., Michelle S. Ginsberg, B. Zhao, et al.. (2008). Assessing changes in tumor size with CT scans in lung cancer: are volumetric measurements better than unidimensional (1D) and bidimensional (2D) assessments?. Journal of Clinical Oncology. 26(15_suppl). 14562–14562.
15.
Kris, Mark G., William Pao, Maureen F. Zakowski, et al.. (2007). D2-01: Prospective trial of preoperative gefitinib to correlate response with EGFR exon 19 and 21 mutations and to select patients for adjuvant gefitinib. Journal of Thoracic Oncology. 2(8). S393–S393.
16.
Kris, Mark G., William Pao, Marc Ladanyi, et al.. (2006). Prospective trial with preoperative gefitinib to correlate lung cancer response with EGFR exon 19 and 21 mutations and to select patients for adjuvant therapy. Journal of Clinical Oncology. 24(18_suppl). 7021–7021.
17.
Zhao, B., et al.. (2006). 81 Development of a computer method for volumetric response assessment in mesothelioma. Lung Cancer. 54. S20–S20.
18.
Riely, Gregory J., Mark G. Kris, Lawrence H. Schwartz, et al.. (2006). Prospective FDG-PET and CT assessment of discontinuation of erlotinib (E) or gefitinib (G) in patients with EGFR TKI sensitive non-small cell lung cancer (NSCLC) who subsequently progress radiographically on E or G (“acquired resistance”) followed by re-initiation of E or G and the subsequent addition of everolimus (RAD001). Journal of Clinical Oncology. 24(18_suppl). 7065–7065.
19.
Abou‐Alfa, Ghassan K., Leonard B. Saltz, B. Zhao, et al.. (2004). Novel methodology of response assessment in hepatocellular carcinoma (HCC) -Assessing response by change in tumor enhancement in distinction from conventional means. Journal of Clinical Oncology. 22(14_suppl). 3107–3107.
20.
Yankelevitz, David F., Anthony P. Reeves, William J. Kostis, B. Zhao, & Claudia I. Henschke. (2000). Small Pulmonary Nodules: Volumetrically Determined Growth Rates Based on CT Evaluation. Radiology. 217(1). 251–256.
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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