Current Search: Gurupur, Varadraj (x)
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- Title
- A deep learning approach to diagnosing schizophrenia.
- Creator
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Barry, Justin, Valliyil Thankachan, Sharma, Gurupur, Varadraj, Jha, Sumit Kumar, Ewetz, Rickard, University of Central Florida
- Abstract / Description
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In this article, the investigators present a new method using a deep learning approach to diagnose schizophrenia. In the experiment presented, the investigators have used a secondary dataset provided by National Institutes of Health. The aforementioned experimentation involves analyzing this dataset for existence of schizophrenia using traditional machine learning approaches such as logistic regression, support vector machine, and random forest. This is followed by application of deep...
Show moreIn this article, the investigators present a new method using a deep learning approach to diagnose schizophrenia. In the experiment presented, the investigators have used a secondary dataset provided by National Institutes of Health. The aforementioned experimentation involves analyzing this dataset for existence of schizophrenia using traditional machine learning approaches such as logistic regression, support vector machine, and random forest. This is followed by application of deep learning techniques using three hidden layers in the model. The results obtained indicate that deep learning provides state-of-the-art accuracy in diagnosing schizophrenia. Based on these observations, there is a possibility that deep learning may provide a paradigm shift in diagnosing schizophrenia.
Show less - Date Issued
- 2019
- Identifier
- CFE0007429, ucf:52737
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007429
- Title
- Social Media as a Healthcare Tool: Case Study Analysis of Factors Influencing Pediatric Clinicians' Behavioral Intent to Adopt Social Media for Patient Communication and Engagement.
- Creator
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Mustonen, Rachel, Hou, Su-I, Malvey, Donna, Gurupur, Varadraj, Wisniewski, Pamela, University of Central Florida
- Abstract / Description
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Social media aids communication among users worldwide. However, a notable gap exist among social media users, healthcare professionals utilizing social media in the work place. While the concept of harnessing social media as a professional tool is not novel, healthcare professionals have yet to embrace the practice as standard workflow. This study identifies factors influencing clinicians' behavioral intent to adopt social media for patient engagement and communication. A new framework, the...
Show moreSocial media aids communication among users worldwide. However, a notable gap exist among social media users, healthcare professionals utilizing social media in the work place. While the concept of harnessing social media as a professional tool is not novel, healthcare professionals have yet to embrace the practice as standard workflow. This study identifies factors influencing clinicians' behavioral intent to adopt social media for patient engagement and communication. A new framework, the Healthcare Social Media Adoption Framework (HSMA), guided this mixed-method approach to assess 7 factors identified by theory and literature as adoption influencers. A custom, web-based survey collected data from 60 full-time, pediatric clinicians (47 quantitative) at the case institution (a pediatric hospital). Additionally, individual interviews of 6 participants provided their prospective on using social media for patient communications and engagement. Results: Privacy concerns were the only statically significant factor; with an inverse relationship to positive adoption intent, indicating higher privacy concerns influence lower behavioral intent to adopt social media for patient engagement and communication. The qualitative analysis revealed privacy concerns encompass two themes, personal privacy for patient and providers (boundaries), and cybersecurity. The qualitative inputs also uncovered perceived unprofessionalism as a new factor influencing clinician adoption. The implications for these findings indicate a need for both healthcare organizations and healthcare regulators to establish cyber-security defenses for security and use protocols for privacy to aid the diffusion and adoption acceptance of social media use by pediatric healthcare professionals. This research has contributed in four areas: 1) fill a knowledge gap by identifying new factors that influence the behavioral intent of pediatric clinicians to adopt social media; 2) confirm/reject behavioral intent influences found in the literature; 3) formulated a new HSMA framework that measures functional, cognitive, and social aspects of social media adoption; and 4) prioritizes policies and global standard focus.
Show less - Date Issued
- 2018
- Identifier
- CFE0007062, ucf:51998
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0007062
- Title
- Factors Influencing Hypoglycemia Care Utilization and Outcomes Among Adult Diabetic Patients Admitted to Hospitals: A Predictive Model.
- Creator
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Kattan, Waleed, Wan, Thomas, Ramirez, Bernardo, Gurupur, Varadraj, Stevenson, Robyne, Pratley, Richard, University of Central Florida
- Abstract / Description
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Diabetes Miletus (DM) is one of the major health problems in the United States. Despite all efforts made to combat this disease, its incidence and prevalence are steadily increasing. One of the common and serious side effects of treatment among people with diabetes is hypoglycemia (HG), where the level of blood glucose falls below the optimum level. Episodes of HG vary in their severity. Nevertheless, many require medical assistance and are usually associated with higher utilization of...
Show moreDiabetes Miletus (DM) is one of the major health problems in the United States. Despite all efforts made to combat this disease, its incidence and prevalence are steadily increasing. One of the common and serious side effects of treatment among people with diabetes is hypoglycemia (HG), where the level of blood glucose falls below the optimum level. Episodes of HG vary in their severity. Nevertheless, many require medical assistance and are usually associated with higher utilization of healthcare resources such as frequent emergency department visits and physician visits. Additionally, patients who experience HG frequently have poor outcomes such as higher rates for morbidities and mortality.Although many studies have been conducted to explore the risk factors associated with HG as well as others that looked into the level of healthcare utilization and outcomes among patients with HG, most of these studies failed to establish a theoretical foundation and integrate a comprehensive list of personal risk factors. Therefore, this study aimed to employ Andersen's health Behavior Model of health care utilization (BM) as a framework to examine the problems of HG. This holistic approach facilitates enumerating predictors and examining differential risks of the predisposing (P), enabling (E) and need-for-care (N) factors influencing HG and their effects on utilization (U) and outcomes (O). The population derived from the national inpatient sample of the Healthcare Cost and Utilization Project (HCUP) database and included all non-pregnant adult diabetic patients admitted to hospitals' Emergency Departments (EDs) with a diagnosis of HG from 2012-2014. Based on the BM framework, different factors influencing HG utilization and outcome were grouped under the P, E, or N component. Utilization was measured by patients' length of stay (LoS) in the hospital and the total charges incurred for the stay. Outcome was assessed based on the severity ranging from mortality (the worst), severe complications, mild complications, to no complications (the best). Structural Equation Modeling (SEM) followed by Decision Tree Regression (DTREG) were performed. SEM helped in testing multiple hypotheses developed in the study as well as exploring the direct and indirect impact of different risk factors on utilization and outcome. The results of the analysis show that N is the most influential component of predictors of U and O. This is parallel to what was repeatedly found in different studies that employed the BM. Regarding the other two components, P was found to have some effect on O, while E influences the total charge. Interaction effects of predictors were noted between some components, which indicate the indirect effect of these components on U and O. Subsequently, DTREG analysis was conducted to further explore the probability of the different predictor variables on LoS, total charge, and outcome. Results of this study revealed that the presence of renal disease and DM complications among HG patients play a key role in predicting U and O. Furthermore, age, socio-economic status (SES), and the geographical location of the patients were also found to be vital factors in determining the variability in U and O among HG patients.In conclusion, findings of this study lend support to the use of the BM approach to health services use and outcomes and provide some practical applications for healthcare providers in terms of using the predictive model for targeting patient subgroups (HG patients) for interventions among diabetic patients. Moreover, policy implications, particularly related to the Central Florida area, for decision makers regarding how to approach the growing problem of DM can be drawn from the study results.
Show less - Date Issued
- 2017
- Identifier
- CFE0006611, ucf:51304
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006611
- Title
- Determinants of hospital efficiency and patient safety in the United States.
- Creator
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Shettian, Kruparaj, Wan, Thomas, Noblin, Alice, Gurupur, Varadraj, Cobb, Enesha, Anderson, Kim, University of Central Florida
- Abstract / Description
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Hospitals engage in undertakings on a continual basis to enhance IT capabilities, diffusion of innovations, hospital-physician integration, and standardization to improve their performance. This empirical study explored the interdependence of three macro-level structural factors and their independent impact on the hospital performance measures efficiency and patient safety, with standardization as an important mediator. The researcher conducted a cross-sectional analysis of multiple data sets...
Show moreHospitals engage in undertakings on a continual basis to enhance IT capabilities, diffusion of innovations, hospital-physician integration, and standardization to improve their performance. This empirical study explored the interdependence of three macro-level structural factors and their independent impact on the hospital performance measures efficiency and patient safety, with standardization as an important mediator. The researcher conducted a cross-sectional analysis of multiple data sets from public user files on the acute care hospital industry. The theoretical underpinnings of the study included the structure-process-outcome theory and institutional isomorphism theory. The statistical analysis comprised confirmatory factor analysis (CFA) and covariance structural equation modeling (SEM). The study comprised data for 2,352 acute care hospitals in the United States, which represented more than half of the hospital population. As expected by the hypotheses, the study demonstrated that IT capability, hospital-physician integration, and innovativeness directly affect the variability in standardization, but they did not directly influence the variation in hospital efficiency and patient safety. This revealed that hospitals should focus on standardization because it is the mediating process between structural variables and performance variables. The results indicated a strong negative influence of standardization on hospital efficiency and a weak positive influence on patient safety. The study confirmed the triadic model that (")structure(") influences the process, which in turn influences organizational outcomes. As standardization through coercive, mimetic, and normative pressure mechanisms becomes more common through system integration and increased collaborative governance, more research on how the implementation of standards may perpetuate isomorphism or uniformity is imperative. The researcher recommends future studies to employ a longitudinal study design to explore the determinants of a variety of performance and outcome indicators, such as patient satisfaction, timeliness of care, the effectiveness of care, and equity/financial performance in addition to patient safety and hospital efficiency.
Show less - Date Issued
- 2017
- Identifier
- CFE0006794, ucf:51810
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006794