Shaimaa Bakr

678 total citations
9 papers, 456 citations indexed

About

Shaimaa Bakr is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Shaimaa Bakr has authored 9 papers receiving a total of 456 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Molecular Biology and 2 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Shaimaa Bakr's work include Radiomics and Machine Learning in Medical Imaging (6 papers), Medical Imaging Techniques and Applications (2 papers) and Single-cell and spatial transcriptomics (2 papers). Shaimaa Bakr is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (6 papers), Medical Imaging Techniques and Applications (2 papers) and Single-cell and spatial transcriptomics (2 papers). Shaimaa Bakr collaborates with scholars based in United States, France and Spain. Shaimaa Bakr's co-authors include Sebastian Echegaray, Sandy Napel, Daniel L. Rubin, Mājid Shafiq, Kelsey Ayers, Weiruo Zhang, Andrew Quon, Sylvia K. Plevritis, Joseph B. Shrager and Ann N. Leung and has published in prestigious journals such as Cancer Research, Scientific Data and Journal of Digital Imaging.

In The Last Decade

Shaimaa Bakr

9 papers receiving 451 citations

Peers

Shaimaa Bakr

RNMI

PRM

AI

ONCOL

MB

Chuan Peng China

Hongna Tan China

An-Hua Li China

Charlie Alexander Hamm Germany

Zhe Jin China

Chao You China

Weicai Huang China

Isabel Schobert Germany

Anup Vinayan United Kingdom

Chuan Peng China

Shaimaa Bakr

170 ×0.5

RNMI

101 ×0.5

PRM

60 ×0.5

AI

123 ×1.6

ONCOL

54 ×0.7

MB

Citations per year, relative to Shaimaa Bakr Shaimaa Bakr (= 1×) peers Chuan Peng

Countries citing papers authored by Shaimaa Bakr

Since Specialization

Citations

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

Fields of papers citing papers by Shaimaa Bakr

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaimaa Bakr

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

All Works

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9 of 9 papers shown

1.

Bakr, Shaimaa, Kevin Brennan, Pritam Mukherjee, et al.. (2023). Identifying key multifunctional components shared by critical cancer and normal liver pathways via SparseGMM. Cell Reports Methods. 3(1). 100392–100392. 1 indexed citations

2.

Gevaert, Olivier, Shaimaa Bakr, Celine Everaert, et al.. (2020). Imaging-AMARETTO: An Imaging Genomics Software Tool to Interrogate Multiomics Networks for Relevance to Radiography and Histopathology Imaging Biomarkers of Clinical Outcomes. JCO Clinical Cancer Informatics. 4(4). 421–435. 9 indexed citations

3.

Mattonen, Sarah A., et al.. (2020). Quantitative imaging feature pipeline: a web-based tool for utilizing, sharing, and building image-processing pipelines. Journal of Medical Imaging. 7(4). 1–1. 16 indexed citations

4.

Bakr, Shaimaa, Olivier Gevaert, Bhavik N. Patel, et al.. (2020). Interreader Variability in Semantic Annotation of Microvascular Invasion in Hepatocellular Carcinoma on Contrast-enhanced Triphasic CT Images. Radiology Imaging Cancer. 2(3). e190062–e190062. 7 indexed citations

5.

Mattonen, Sarah A., Guido Davidzon, Shaimaa Bakr, et al.. (2019). [18F] FDG Positron Emission Tomography (PET) Tumor and Penumbra Imaging Features Predict Recurrence in Non–Small Cell Lung Cancer. Tomography. 5(1). 145–153. 27 indexed citations

6.

Zhang, Weiruo, Mājid Shafiq, Mehran Jamali, et al.. (2018). GFPT2 -Expressing Cancer-Associated Fibroblasts Mediate Metabolic Reprogramming in Human Lung Adenocarcinoma. Cancer Research. 78(13). 3445–3457. 87 indexed citations

7.

Bakr, Shaimaa, Olivier Gevaert, Sebastian Echegaray, et al.. (2018). A radiogenomic dataset of non-small cell lung cancer. Scientific Data. 5(1). 180202–180202. 209 indexed citations

8.

Echegaray, Sebastian, Shaimaa Bakr, Daniel L. Rubin, & Sandy Napel. (2017). Quantitative Image Feature Engine (QIFE): an Open-Source, Modular Engine for 3D Quantitative Feature Extraction from Volumetric Medical Images. Journal of Digital Imaging. 31(4). 403–414. 40 indexed citations

9.

Bakr, Shaimaa, Sebastian Echegaray, Rajesh P. Shah, Aya Kamaya, & John D. Louie. (2017). Noninvasive radiomics signature based on quantitative analysis of computed tomography images as a surrogate for microvascular invasion in hepatocellular carcinoma: a pilot study. Journal of Medical Imaging. 4(4). 1–1. 60 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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