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Predictive Modeling Of Influenza In New England Using A Recurrent Deep Neural Network, Alfred Amendolara
Predictive Modeling Of Influenza In New England Using A Recurrent Deep Neural Network, Alfred Amendolara
Theses
Predicting seasonal variation in influenza epidemics is an ongoing challenge. To better predict seasonal influenza and provide early warning of pandemics, a novel approach to Influenza-Like-Illness (ILI) prediction was developed. This approach combined a deep neural network with ILI, climate, and population data. A predictive model was created using a deep neural network based on TensorFlow 2.0 Beta. The model used Long-Short Term Memory (LSTM) nodes. Data was collected from the Center for Disease Control, the National Center for Environmental Information (NCEI) and the United States Census Bureau. These parameters were temperature, precipitation, wind speed, population size, vaccination rate and …
Extracting Patterns In Medical Claims Data For Predicting Opioid Overdose, Ryan Sanders
Extracting Patterns In Medical Claims Data For Predicting Opioid Overdose, Ryan Sanders
Graduate Theses and Dissertations
The goal of this project is to develop an efficient methodology for extracting features from time-dependent variables in transaction data. Transaction data is collected at varying time intervals making feature extraction more difficult. Unsupervised representational learning techniques are investigated, and the results compared with those from other feature engineering techniques. A successful methodology provides features that improve the accuracy of any machine learning technique. This methodology is then applied to insurance claims data in order to find features to predict whether a patient is at risk of overdosing on opioids. This data covers prescription, inpatient, and outpatient transactions. Features created …
Parkinsonian Speech And Voice Quality: Assessment And Improvement, Amr Gaballah
Parkinsonian Speech And Voice Quality: Assessment And Improvement, Amr Gaballah
Electronic Thesis and Dissertation Repository
Parkinson’s disease (PD) is the second most common neurodegenerative disease. Statistics show that nearly 90% of people impaired with PD develop voice and speech disorders. Speech production impairments in PD subjects typically result in hypophonia and consequently, poor speech signal-to-noise ratio (SNR) in noisy environments and inferior speech intelligibility and quality. Assessment, monitoring, and improvement of the perceived quality and intelligibility of Parkinsonian voice and speech are, therefore, paramount. In the first study of this thesis, the perceived quality of sustained vowels produced by PD patients was assessed through objective predictors. Subjective quality ratings of sustained vowels were collected from …
The Role Of Movement Pattern In Relation To Running Related Injuries Risk Factors, Marwan Mahmoud A Aljohani
The Role Of Movement Pattern In Relation To Running Related Injuries Risk Factors, Marwan Mahmoud A Aljohani
Dissertations (1934 -)
About 52.3 million American run on a regular basis. Up to 79% of runners get injured every year and the rate of injury has not declined over the past decades. Females have twice the risk of developing a running related injury (RRI). Rate of loading (ROL), tibial impact shock (TIS), and low movement variability may contribute to the development of RRI. Not much is known, however, about the relationships between impact kinetics (i.e. ROL, TIS) and movement variability. In addition, there is a lack of understanding about the effects of sex and speed on the aforementioned RRI risk factors. Therefore, …
Data Patterns Discovery Using Unsupervised Learning, Rachel A. Lewis
Data Patterns Discovery Using Unsupervised Learning, Rachel A. Lewis
Electronic Theses and Dissertations
Self-care activities classification poses significant challenges in identifying children’s unique functional abilities and needs within the exceptional children healthcare system. The accuracy of diagnosing a child's self-care problem, such as toileting or dressing, is highly influenced by an occupational therapists’ experience and time constraints. Thus, there is a need for objective means to detect and predict in advance the self-care problems of children with physical and motor disabilities. We use clustering to discover interesting information from self-care problems, perform automatic classification of binary data, and discover outliers. The advantages are twofold: the advancement of knowledge on identifying self-care problems in …
Predictors And Health Outcomes Of Treatment-Resistant Depression Among Adults With Chronic Non-Cancer Pain Conditions And Major Depressive Disorder, Drishti Shah
Graduate Theses, Dissertations, and Problem Reports
Understanding major depressive disorder (MDD) as a comorbidity in patients with chronic non-cancer pain conditions (CNPC) is of importance because of the high prevalence and well documented bi-directional relationship between MDD and pain. Furthermore, presence of CNPC among adults with MDD often reduces benefits of antidepressant therapy, thereby increasing the possibility of treatment resistance. Treatment-resistant depression (TRD) commonly defined as insufficient response to multiple antidepressant trials, often worsens depression and pain symptoms and can amplify the clinical and economic burden among adults with CNPC and MDD. Additionally, long-term opioid therapy (LTOT) may be prescribed at a higher rate to adults …