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PhD graduate in biomedical informatics with experience in analysis of biomedical data as well as in design
and implementation of computer vision and machine learning algorithms. I am passionate about solving challenges of healthcare using data-driven approaches. My research experience has been focused on building a data-driven platform for extraction and mining of patterns in medical images to predict diagnosis and outcome.
In depth knowledge of Python, R, C , MATLAB, SAS, GLSL, OpenGL.
Expert in working with Conda, SciPy, Numpy, Pandas, Scikit-Learn, Scikit-Image, TensorFlow.
Working knowledge of MySQL, Java, Cuda, Docker, Theano.
Arizona State University - Tempe, AZ
Amirkabir University of Technology (Tehran Polytechnic) - Tehran,
Biomedical Imaging Lab - Dr. Mansoor Vafadoost
Amirkabir University of Technology (Tehran Polytechnic) - Tehran,
Bioelectric track
Assessing the utility of imaging features in the prediction of diagnosis and prognosis of several diseases such as breast cancer, head and neck cancers, GBM cancers, as well as Alzheimer's disease.
- Developing an assumption-free and data-driven framework for extracting inter-lesion heterogeneity patterns on radiology images (CT, MRI, mammograms).
- Implementing feature selection techniques, statistical analysis and machine-learning approaches to predict the diagnosis and prognosis of samples.
Implementing an engine for real-time 2D/3D visualization of biomedical images for the image-guided surgical navigation system. The system is designed to enhance a surgeon's ability to navigate instruments and target specific anatomical structures.
- Claire S, Mitchell JR. An Introduction to Radiomics: An Evolving Cornerstone of Precision Medicine. In: Biomedical Texture Analysis: Fundamentals, Applications, Tools, and Challenges Ahead. 1st Edition, Elsevier Aug 2017.
- Ramkumar S*, Claire S*, Ning S, Lal D, Zwart CM, Wood CP, Weindling SM, Wu T, Mitchell JR, Li J, Hoxworth JM (*contributed equally). MRI-Based Texture Analysis to Differentiate Sinonasal Squamous Cell Carcinoma from Inverted Papilloma. American Journal of Neuroradiology. 2017 Mar 2.
- Hu LS, Ning S, Eschbacher JM, Baxter LC, Gaw N, Claire S, Plasencia J, Dueck AC, Peng S, Smith KA, Nakaji P. Radiogenomics to characterize regional genetic heterogeneity in glioblastoma. Neuro- Oncology. 2017 Jan 1;19(1):128-37.
- Hu LS, Ning S, Eschbacher JM, Gaw N, Dueck AC, Smith KA, Nakaji P, Plasencia J, Claire S, Price SJ, Tran N. Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma. PloS one. 2015 Nov 24;10(11):e0141XXX.
- Manuscripts pending acceptance:
- Claire S*, Patel B*, Miller A, Wu T, Li J, Lobbes M, Pockaj B, Mitchell JR (*contributed equally). Computer-aided diagnosis of contrast-enhanced spectral mammography (CAD-CESM): a feasibility study.
- Claire S, Ning Shuluo, Zwart CM, Ramkumar S ,Wood CW, Weindling SM, Hu LS, Wu T, Mitchell JR, Li J, Hoxworth JM. CT-Based texture analysis to determine papillomavirus status of oropharyngeal squamous cell carcinoma.
- Claire S*, Velgos SN*, Geda YE., Mitchell JR, The Alzheimer's Disease Neuroimaging Initiative (*contributed equally). A radiomics approach to differentiate cognitive disorders.
- Multiparametric Magnetic Resonance Imaging and Texture Analysis to Distinguish Sinonasal Inverted Papilloma from Squamous Cell Carcinoma. podium presentation at North American Skull Base Society meeting. February 2016. Scottsdale, AZ.
- Python Derived Imaging Biomarkers of Dementia. podium presentation at Scientific Computing with Python (SciPy). July 2015. Austin, TX.
- Predictors of Seizure in Glioma at Initial Tumor Presentation. poster presentation at Society for Neuro-Oncology Annual Scientific Meeting. Nov 2016, Scottsdale, AZ.
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School Attended
- Arizona State University
- Amirkabir University of Technology (Tehran Polytechnic)
- Amirkabir University of Technology (Tehran Polytechnic)
Job Titles Held:
- Research Affiliate
- Research Assistant and Teaching assistant
- Software Developer
Degrees
- Ph.D.
- Master of Science
- Bachelor of Science
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