Shariq Mohammed

442 total citations
25 papers, 229 citations indexed

About

Shariq Mohammed is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Genetics. According to data from OpenAlex, Shariq Mohammed has authored 25 papers receiving a total of 229 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Molecular Biology and 4 papers in Genetics. Recurrent topics in Shariq Mohammed's work include Radiomics and Machine Learning in Medical Imaging (9 papers), Glioma Diagnosis and Treatment (4 papers) and MRI in cancer diagnosis (3 papers). Shariq Mohammed is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), Glioma Diagnosis and Treatment (4 papers) and MRI in cancer diagnosis (3 papers). Shariq Mohammed collaborates with scholars based in United States, Canada and India. Shariq Mohammed's co-authors include Arvind Rao, Veerabhadran Baladandayuthapani, Clement C. Tham, Dennis S.C. Lam, Christopher Kai-Shun Leung, Bhramar Mukherjee, Maxwell Salvatore, Sevcan Türk, Daniel Barker and John Kim and has published in prestigious journals such as SHILAP Revista de lepidopterología, Annals of Neurology and Scientific Reports.

In The Last Decade

Shariq Mohammed

19 papers receiving 225 citations

Peers

Shariq Mohammed

RNMI

GENET

OPHTH

Raphael Sonabend United Kingdom

Siping Luo China

Georgina Maalouf France

Wenzhu Song China

Dan Gong United States

Juanjuan Fan United States

Noelia García Barrio Spain

Minyan Zeng China

Lushan Xiao China

Raphael Sonabend United Kingdom

Shariq Mohammed

30 ×0.3

RNMI

31 ×0.6

5 ×0.1

GENET

2 ×0.1

OPHTH

7 ×0.2

Citations per year, relative to Shariq Mohammed Shariq Mohammed (= 1×) peers Raphael Sonabend

Countries citing papers authored by Shariq Mohammed

Since Specialization

Citations

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

Fields of papers citing papers by Shariq Mohammed

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shariq Mohammed

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

All Works

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20 of 20 papers shown

Cervantes‐Arslanian, Anna M., Emelia J. Benjamin, Emily J. Gilmore, et al.. (2025). Quantitative Pupillometry Predicts Neurologic Deterioration in Patients with Large Middle Cerebral Artery Stroke. Annals of Neurology. 97(5). 930–941.

Song, Jonathan J, Stelios M. Smirnakis, Emily J. Gilmore, et al.. (2025). Later midline shift is associated with better post-hospitalization discharge status after large middle cerebral artery stroke. Scientific Reports. 15(1). 11738–11738.

Mohammed, Shariq, et al.. (2024). Statistical Analysis of Quantitative Cancer Imaging Data. 1(1). 2 indexed citations

LaValley, Michael P., Kimberly A. Dukes, Kevin Lane, et al.. (2024). Modeling health and well-being measures using ZIP code spatial neighborhood patterns. Scientific Reports. 14(1). 9180–9180. 3 indexed citations

Mohammed, Shariq, et al.. (2023). Tumor radiogenomics in gliomas with Bayesian layered variable selection. Medical Image Analysis. 90. 102964–102964. 2 indexed citations

Warner, Elisa, Joonsang Lee, Nicholas Wang, et al.. (2023). Low-parameter supervised learning models can discriminate pseudoprogression and true progression in non-perfusion-based MRI. PubMed. 2023. 1–4.

Mohammed, Shariq, et al.. (2023). Bayesian Variable Selection in Double Generalized Linear Tweedie Spatial Process Models. arXiv (Cornell University). 187–199.

Chekouo, Thierry, Francesco C. Stingo, Shariq Mohammed, Arvind Rao, & Veerabhadran Baladandayuthapani. (2023). A Bayesian group selection with compositional responses for analysis of radiologic tumor proportions and their genomic determinants. The Annals of Applied Statistics. 17(4). 1 indexed citations

Türk, Sevcan, Nicholas Wang, Shariq Mohammed, et al.. (2022). Comparative study of radiologists vs machine learning in differentiating biopsy-proven pseudoprogression and true progression in diffuse gliomas. SHILAP Revista de lepidopterología. 2(3). 100088–100088. 3 indexed citations

10.

Mohammed, Shariq, et al.. (2022). Integrative Bayesian Models Using Post-Selective Inference: A Case Study in Radiogenomics. Biometrics. 79(3). 1801–1813. 7 indexed citations

11.

Mohammed, Shariq, et al.. (2022). GaWRDenMap: a quantitative framework to study the local variation in cell–cell interactions in pancreatic disease subtypes. Scientific Reports. 12(1). 3708–3708. 4 indexed citations

12.

Qin, Angel, Fatima Lima, Samantha L. Bell, et al.. (2022). Cellular engagement and interaction in the tumor microenvironment predict non-response to PD-1/PD-L1 inhibitors in metastatic non-small cell lung cancer. Scientific Reports. 12(1). 9054–9054. 8 indexed citations

13.

Mohammed, Shariq. (2022). Critical Analysis of Banking Sector Reforms in India with Special Emphasis on Technological Advancement. 12(1). 20–36.

14.

Mohammed, Shariq, et al.. (2021). Spatial Tweedie exponential dispersion models: an application to insurance rate-making. Scandinavian Actuarial Journal. 2021(10). 1017–1036. 5 indexed citations

15.

Mohammed, Shariq & Dipak K. Dey. (2021). Scalable spatio‐temporal Bayesian analysis of high‐dimensional electroencephalography data. Canadian Journal of Statistics. 49(1). 107–128.

16.

Mohammed, Shariq, Tingyang Li, Elisa Warner, et al.. (2020). Density-based classification in diabetic retinopathy through thickness of retinal layers from optical coherence tomography. Scientific Reports. 10(1). 15937–15937. 10 indexed citations

17.

Lee, Joonsang, Nicholas Wang, Sevcan Türk, et al.. (2020). Discriminating pseudoprogression and true progression in diffuse infiltrating glioma using multi-parametric MRI data through deep learning. Scientific Reports. 10(1). 20331–20331. 49 indexed citations

18.

Chekouo, Thierry, Shariq Mohammed, & Arvind Rao. (2020). A Bayesian 2D functional linear model for gray-level co-occurrence matrices in texture analysis of lower grade gliomas. NeuroImage Clinical. 28. 102437–102437. 12 indexed citations

19.

Mohammed, Shariq, et al.. (2018). A Hybrid (ACO-PSO) Algorithm Based on Maximum Power Point Tracking and its Performance Improvement within Shadow Conditions. International Journal of Engineering & Technology. 7(4.37). 43–47. 1 indexed citations

20.

Leung, Christopher Kai-Shun, et al.. (2006). In vivo measurements of macular and nerve fibre layer thickness in retinal arterial occlusion. Eye. 21(12). 1464–1468. 36 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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