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Articles 1 - 2 of 2
Full-Text Articles in Other Analytical, Diagnostic and Therapeutic Techniques and Equipment
Cardiovascular Disease Prediction Modelling: A Machine Learning Approach, Usmaan Al-Shehab, Maduka Gunasinghe, Yousuf Elkhoga, Nimay Patel, Juliana Yang
Cardiovascular Disease Prediction Modelling: A Machine Learning Approach, Usmaan Al-Shehab, Maduka Gunasinghe, Yousuf Elkhoga, Nimay Patel, Juliana Yang
Rowan-Virtua Research Day
The objective of this project is to utilize the UCI Heart Disease dataset to identify physiological biomarkers that are highly correlated with heart disease incidence. A predictive model can then be developed using these biomarkers to estimate the likelihood of someone having or developing a heart-related condition. This study compares the efficacy of predicting cardiovascular disease as an outcome using three machine learning algorithms: Support Vector Machine, Gaussian Naive Bayes, and logistic regression. Support Vector Machine works by creating hyperplanes between data points to conduct classification. Gaussian Naive Bayes works by using the conditional probabilities of events to classify the …
Hdqlife: Development And Assessment Of Health-Related Quality Of Life In Huntington Disease (Hd), N E Carlozzi, S G Schilling, J-S Lai, J S Paulsen, E A Hahn, J S Perlmutter, C A Ross, N R Downing, A L Kratz, M K Mccormack, M A Nance, K A Quaid, J C Stout, R C Gershon, R E Ready, J A Miner, S K Barton, S L Perlman, S M Rao, S Frank, I Shoulson, H Marin, M D Geschwind, P Dayalu, S M Goodnight, D Cella
Hdqlife: Development And Assessment Of Health-Related Quality Of Life In Huntington Disease (Hd), N E Carlozzi, S G Schilling, J-S Lai, J S Paulsen, E A Hahn, J S Perlmutter, C A Ross, N R Downing, A L Kratz, M K Mccormack, M A Nance, K A Quaid, J C Stout, R C Gershon, R E Ready, J A Miner, S K Barton, S L Perlman, S M Rao, S Frank, I Shoulson, H Marin, M D Geschwind, P Dayalu, S M Goodnight, D Cella
Rowan-Virtua School of Osteopathic Medicine Faculty Scholarship
PURPOSE: Huntington disease (HD) is a chronic, debilitating genetic disease that affects physical, emotional, cognitive, and social health. Existing patient-reported outcomes (PROs) of health-related quality of life (HRQOL) used in HD are neither comprehensive, nor do they adequately account for clinically meaningful changes in function. While new PROs examining HRQOL (i.e., Neuro-QoL-Quality of Life in Neurological Disorders and PROMIS-Patient-Reported Outcomes Measurement Information System) offer solutions to many of these shortcomings, they do not include HD-specific content, nor have they been validated in HD. HDQLIFE addresses this by validating 12 PROMIS/Neuro-QoL domains in individuals with HD and by using established PROMIS …