Sam Payabvash, MD
Associate Professor of Radiology and Biomedical ImagingCards
About
Research
Overview
Stroke imaging: Devising prognostic model for stroke patients based on the location of brain parenchymal damage on initial scans. Application of deep neural networks for identification of acute infarct on head CT, localization of arterial occlusion, and grading of arterial collaterals on admission CT angiography. Outcome prediction based on imaging patterns of hemorrhagic stroke.
Head and neck cancers: Applying texture analysis, radiomics and machine-learning models for differentiation of neoplasms, prediction of molecular subtypes, and prognostication beyond current staging schemes based on CT, MRI, and PET scans in patients with tumors of brain and neck.
Brain connectivity in neurodevelopmental disorders: Examining the functional and microstructural connectivity of the brain in children at risk of autism and neurodevelopmental disorders based on diffusion tensor imaging and tractography. Using machine learning models to devise bioimaging biomarkers for neurodevelopmental disease based on quantitative metrics of brain connectivity.
Medical Subject Headings (MeSH)
Academic Achievements & Community Involvement
Clinical Care
Overview
Clinical Specialties
Board Certifications
Neuroradiology
- Certification Organization
- AB of Radiology
- Original Certification Date
- 2018
Diagnostic Radiology
- Certification Organization
- AB of Radiology
- Original Certification Date
- 2017
News
News
- February 08, 2023
Santiago Clocchiatti-Tuozzo, MD Honored with Bernard J. Tyson Career Development Award and Stroke Underrepresented Racial and Ethnic Groups Travel Grant
- November 27, 2022Source: YaleNews
Higher Weight Is Linked to Poor Brain Health in Children
- November 27, 2022Source: RSNA
Obesity Linked to Poor Brain Health in Children
- November 22, 2022Source: YaleNews
Neuromarker for ADHD Could Improve Diagnosis of the Disorder