Open Access. Powered by Scholars. Published by Universities.®
- Discipline
Articles 1 - 2 of 2
Full-Text Articles in Medicine and Health Sciences
Classification Models Of Idiopathic Pulmonary Fibrosis Patients, Mohammed Alqawba, Luis R. Rodriguez, Norou Diawara, Rebecca T. Beuschel, Maryann Kaler, Amisha V. Barochia, Stewart J. Levine, Steven D. Nathan, Geraldine Grant
Classification Models Of Idiopathic Pulmonary Fibrosis Patients, Mohammed Alqawba, Luis R. Rodriguez, Norou Diawara, Rebecca T. Beuschel, Maryann Kaler, Amisha V. Barochia, Stewart J. Levine, Steven D. Nathan, Geraldine Grant
Mathematics & Statistics Faculty Publications
Idiopathic pulmonary fibrosis (IPF) is a chronic and fatal interstitial lung disease with no current cure. Progression of IPF is difficult to predict as the clinical course can be highly variable and range from a rapidly deteriorating state to a relatively stable state, or may be characterized by a slow progressive decline. Therefore, the need for an accurate diagnosis and improved tools for monitoring and managing IPF is of paramount importance, all for understanding the mitochondrial structure and the function played in the IPF. Mitochondrial DNA copy number (MtDCN) has been correlated with mortality in IPF patients and is a …
Prediction Of Molecular Mutations In Diffuse Low-Grade Gliomas Using Mr Imaging Features, Zeina A. Shboul, James Chen, Khan M. Iftekharrudin
Prediction Of Molecular Mutations In Diffuse Low-Grade Gliomas Using Mr Imaging Features, Zeina A. Shboul, James Chen, Khan M. Iftekharrudin
Electrical & Computer Engineering Faculty Publications
Diffuse low-grade gliomas (LGG) have been reclassified based on molecular mutations, which require invasive tumor tissue sampling. Tissue sampling by biopsy may be limited by sampling error, whereas non-invasive imaging can evaluate the entirety of a tumor. This study presents a non-invasive analysis of low-grade gliomas using imaging features based on the updated classification. We introduce molecular (MGMT methylation, IDH mutation, 1p/19q co-deletion, ATRX mutation, and TERT mutations) prediction methods of low-grade gliomas with imaging. Imaging features are extracted from magnetic resonance imaging data and include texture features, fractal and multi-resolution fractal texture features, and volumetric features. Training models include …