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Articles 1 - 4 of 4
Full-Text Articles in Other Medical Sciences
Development, Validation, And Diagnostic Performance Of A Novel Radiomic Model For Predicting Prostate Cancer Recurrence, Linda M. Huynh
Development, Validation, And Diagnostic Performance Of A Novel Radiomic Model For Predicting Prostate Cancer Recurrence, Linda M. Huynh
Theses & Dissertations
Multi-parametric magnetic resonance imaging (MP-MRI)-derived radiomics have been shown to capture sub-visual patterns for the quantitative characterization of prostate cancer (PC) phenotypes. The present dissertation seeks to develop, evaluate, and compare the performance of an MRI-derived radiomic model for the prediction of PC recurrence following definitive treatment with radical prostatectomy (RP).
MP-MRI was obtained from 339 patients who had a minimum of 2 years follow-up following RP at three institutions. The prostate was manually delineated as the region of interest and 924 radiomic features were extracted. All features were evaluated for stability via intraclass correlation coefficient (ICC) and image normalization …
Exploration Of Data Science Toolbox And Predictive Models To Detect And Prevent Medicare Fraud, Waste, And Abuse, Benjamin P. Goodwin, Adam Canton, Babatunde Olanipekun
Exploration Of Data Science Toolbox And Predictive Models To Detect And Prevent Medicare Fraud, Waste, And Abuse, Benjamin P. Goodwin, Adam Canton, Babatunde Olanipekun
SMU Data Science Review
The Federal Department of Health and Human Services spends approximately $830 Billion annually on Medicare of which an estimated $30 to $110 billion is some form of fraud, waste, or abuse (FWA). Despite the Federal Government’s ongoing auditing efforts, fraud, waste, and abuse is rampant and requires modern machine learning approaches to generalize and detect such patterns. New and novel machine learning algorithms offer hope to help detect fraud, waste, and abuse. The existence of publicly accessible datasets complied by The Centers for Medicare & Medicaid Services (CMS) contain vast quantities of structured data. This data, coupled with industry standardized …
Methods Development In Inflammatory Bowel Disease, Andrew B. Steimke
Methods Development In Inflammatory Bowel Disease, Andrew B. Steimke
Theses and Dissertations (ETD)
Inflammatory bowel disease (IBD) is a disease that is classified into two subtypes: ulcerative colitis (UC) and Crohn’s disease (CD). Symptoms can range from mild discomfort to requiring surgical intervention and affects approximately 1-in-200 adults in America alone, with global incidence rates increasing. While many treatments exist for IBD, perhaps the main reason for the lack of a cure is that there are many different pathogeneses that all lead to a very similar expression of symptoms. Over 240 IBD loci have been identified to date, yet the causative allele that drives the association has only been identified in ~60 of …
Investigation Of Radiation Injury In The Esophagus From Definitive Chemoradiation Therapy Using Novel Imaging Biomarkers, Joshua S. Niedzielski
Investigation Of Radiation Injury In The Esophagus From Definitive Chemoradiation Therapy Using Novel Imaging Biomarkers, Joshua S. Niedzielski
Dissertations and Theses (Open Access)
Radiation injury in the esophagus occurs with high frequency from the treatment of non-small cell lung cancer (NSCLC). Radiation esophagitis is an acute normal tissue toxicity that negatively affects treatment efficacy by limiting dose and potentially interrupting radiation therapy. Clinical quantification of this toxicity is typically achieved by utilizing physician grading scales, assigning complication severity on an ordinal scale of symptom presentation and/or physician chosen interventions. These criteria are subjective in nature, both from the physician assigning the grade and the patient reporting the symptom. Furthermore, radiation therapy planning guidelines for the esophagus are derived from toxicity prediction models utilizing …