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Applications Of Machine Learning Methods In Health Outcomes Research: Heart Failure In Women, Khalid Abdullah Alhussain
Applications Of Machine Learning Methods In Health Outcomes Research: Heart Failure In Women, Khalid Abdullah Alhussain
Graduate Theses, Dissertations, and Problem Reports
There is robust evidence that heart failure (HF) is associated with substantial mortality, morbidity, poor health-related quality of life, healthcare utilization, and economic burden. Previous research has revealed that there are sex differences in the epidemiology, etiology, and disease burden of HF. However, research on HF among women, especially postmenopausal women, is limited. To fill the knowledge gap, the three related aims of this dissertation were to: (1) identify knowledge gaps in HF research among women, especially postmenopausal women, using unsupervised machine learning methods and big data (i.e., articles published in PubMed); (2) identify emerging predictors (i.e., polypharmacy and some …