Matching Items (68)
![152165-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-08/152165-Thumbnail%20Image.png?versionId=i15TuqnM5VkYuXA287QXXeDGkbjbg3TO&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240601/us-west-2/s3/aws4_request&X-Amz-Date=20240601T055849Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=67c918cbbb3ec58384fc2ef3a340d90d1a0c2f5eb6a40ee78a1c1e41abef7bf0&itok=MIcep070)
Description
Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.
ContributorsIslam, Gazi (Author) / Li, Baoxin (Thesis advisor) / Liang, Jianming (Thesis advisor) / Dinu, Valentin (Committee member) / Greenes, Robert (Committee member) / Smith, Marshall (Committee member) / Kahol, Kanav (Committee member) / Patel, Vimla L. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
![150897-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-09/150897-Thumbnail%20Image.png?versionId=pejAg.iAQGGAB7HeyTsCzyXSPEDN8EDC&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240605/us-west-2/s3/aws4_request&X-Amz-Date=20240605T232204Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=dd62a4017f513c5b889cef888dbe1fa917fd149d81572034918809266495e46f&itok=-zjM8Dvj)
Description
The living world we inhabit and observe is extraordinarily complex. From the perspective of a person analyzing data about the living world, complexity is most commonly encountered in two forms: 1) in the sheer size of the datasets that must be analyzed and the physical number of mathematical computations necessary to obtain an answer and 2) in the underlying structure of the data, which does not conform to classical normal theory statistical assumptions and includes clustering and unobserved latent constructs. Until recently, the methods and tools necessary to effectively address the complexity of biomedical data were not ordinarily available. The utility of four methods--High Performance Computing, Monte Carlo Simulations, Multi-Level Modeling and Structural Equation Modeling--designed to help make sense of complex biomedical data are presented here.
ContributorsBrown, Justin Reed (Author) / Dinu, Valentin (Thesis advisor) / Johnson, William (Committee member) / Petitti, Diana (Committee member) / Arizona State University (Publisher)
Created2012
![151020-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-08/151020-Thumbnail%20Image.png?versionId=12mTV7J3plsZ8Lin1FNhEDuJ1Y5ssO3Q&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240606/us-west-2/s3/aws4_request&X-Amz-Date=20240606T084725Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=28d3203d5791fe18261c3f79648334d590752e5bc9a684147310ea6c6fd48e38&itok=WRePeP5o)
Description
Critical care environments are complex in nature. Fluctuating team dynamics and the plethora of technology and equipment create unforeseen demands on clinicians. Such environments become chaotic very quickly due to the chronic exposure to unpredictable clusters of events. In order to cope with this complexity, clinicians tend to develop ad-hoc adaptations to function in an effective manner. It is these adaptations or "deviations" from expected behaviors that provide insight into the processes that shape the overall behavior of the complex system. The research described in this manuscript examines the cognitive basis of clinicians' adaptive mechanisms and presents a methodology for studying the same. Examining interactions in complex systems is difficult due to the disassociation between the nature of the environment and the tools available to analyze underlying processes. In this work, the use of a mixed methodology framework to study trauma critical care, a complex environment, is presented. The hybrid framework supplements existing methods of data collection (qualitative observations) with quantitative methods (use of electronic tags) to capture activities in the complex system. Quantitative models of activities (using Hidden Markov Modeling) and theoretical models of deviations were developed to support this mixed methodology framework. The quantitative activity models developed were tested with a set of fifteen simulated activities that represent workflow in trauma care. A mean recognition rate of 87.5% was obtained in automatically recognizing activities. Theoretical models, on the other hand, were developed using field observations of 30 trauma cases. The analysis of the classification schema (with substantial inter-rater reliability) and 161 deviations identified shows that expertise and role played by the clinician in the trauma team influences the nature of deviations made (p<0.01). The results shows that while expert clinicians deviate to innovate, deviations of novices often result in errors. Experts' flexibility and adaptiveness allow their deviations to generate innovative ideas, in particular when dynamic adjustments are required in complex situations. The findings suggest that while adherence to protocols and standards is important for novice practitioners to reduce medical errors and ensure patient safety, there is strong need for training novices in coping with complex situations as well.
ContributorsVankipuram, Mithra (Author) / Greenes, Robert A (Thesis advisor) / Patel, Vimla L. (Thesis advisor) / Petitti, Diana B. (Committee member) / Dinu, Valentin (Committee member) / Smith, Marshall L. (Committee member) / Arizona State University (Publisher)
Created2012
![150708-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-09/150708-Thumbnail%20Image.png?versionId=wXPoc_cAKyhxHOwIFbyXPfxa46NsKdfI&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240605/us-west-2/s3/aws4_request&X-Amz-Date=20240605T232204Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=7d47811fb2961f530e753a8110d6e0f51d4cb83b7c097789cd9a0be2da48cc60&itok=fvJHaiTi)
Description
This work involved the analysis of a public health system, and the design, development and deployment of enterprise informatics architecture, and sustainable community methods to address problems with the current public health system. Specifically, assessment of the Nationally Notifiable Disease Surveillance System (NNDSS) was instrumental in forming the design of the current implementation at the Southern Nevada Health District (SNHD). The result of the system deployment at SNHD was considered as a basis for projecting the practical application and benefits of an enterprise architecture. This approach has resulted in a sustainable platform to enhance the practice of public health by improving the quality and timeliness of data, effectiveness of an investigation, and reporting across the continuum.
ContributorsKriseman, Jeffrey Michael (Author) / Dinu, Valentin (Thesis advisor) / Greenes, Robert (Committee member) / Johnson, William (Committee member) / Arizona State University (Publisher)
Created2012
![151234-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-09/151234-Thumbnail%20Image.png?versionId=uxKFr5XfzgM8dA8I7xsv581tqFxSpqXs&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240606/us-west-2/s3/aws4_request&X-Amz-Date=20240606T015825Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=64973332f6c5ab51ec6665cd6529440a26b0f96ad7bec67c0b705946a2ad0913&itok=Md4w2CIN)
Description
Immunosignaturing is a technology that allows the humoral immune response to be observed through the binding of antibodies to random sequence peptides. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides in a multiplexed fashion. There are computational and statistical challenges to the analysis of immunosignaturing data. The overall aim of my dissertation is to develop novel computational and statistical methods for immunosignaturing data to access its potential for diagnostics and drug discovery. Firstly, I discovered that a classification algorithm Naive Bayes which leverages the biological independence of the probes on our array in such a way as to gather more information outperforms other classification algorithms due to speed and accuracy. Secondly, using this classifier, I then tested the specificity and sensitivity of immunosignaturing platform for its ability to resolve four different diseases (pancreatic cancer, pancreatitis, type 2 diabetes and panIN) that target the same organ (pancreas). These diseases were separated with >90% specificity from controls and from each other. Thirdly, I observed that the immunosignature of type 2 diabetes and cardiovascular complications are unique, consistent, and reproducible and can be separated by 100% accuracy from controls. But when these two complications arise in the same person, the resultant immunosignature is quite different in that of individuals with only one disease. I developed a method to trace back from informative random peptides in disease signatures to the potential antigen(s). Hence, I built a decipher system to trace random peptides in type 1 diabetes immunosignature to known antigens. Immunosignaturing, unlike the ELISA, has the ability to not only detect the presence of response but also absence of response during a disease. I observed, not only higher but also lower peptides intensities can be mapped to antigens in type 1 diabetes. To study immunosignaturing potential for population diagnostics, I studied effect of age, gender and geographical location on immunosignaturing data. For its potential to be a health monitoring technology, I proposed a single metric Coefficient of Variation that has shown potential to change significantly when a person enters a disease state.
ContributorsKukreja, Muskan (Author) / Johnston, Stephen Albert (Thesis advisor) / Stafford, Phillip (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Introduction/Purpose: the purpose of this study was to explore the perception of care after stillbirth and the use of physical activity and/or mindful approaches (e.g., yoga) to cope with grief in women of racial/ethnic minority who have experienced stillbirth.
Methods: This was an exploratory qualitative research study. Participants were African American, Hispanic, Asian, and American Indian women, between the ages of 26 and 38, who have experienced stillbirth within the past 3 years. Participants completed a 20-30 minute phone interview.
Results: Fourteen women participated in the study (M age = 31.02 ± 5.97 years; M time since stillbirth = 1.47 ± 0.94 years). Women’s perceptions about physical activity and mindfulness to cope with grief were coded into the following major themes: perception of health care after stillbirth (satisfaction with the level of care provided), recommendations about inter-conception health care from physician (relating to mental, emotional, and physical health), grief (comfort with communicating with the physician), coping mechanisms, perception of the relationship between physical activity and mood, barriers to participating in physical activity (social and behavioral), pre-pregnancy physical activity, and perception of mindful approach (e.g., yoga) as a coping mechanism.
Conclusion: This was the first study to explore perceptions of health care and the use of physical activity and/or mindful approaches (e.g., yoga) to cope with grief after stillbirth in women of racial/ethnic minority. Findings from this study may help inform health care professionals alter their care practices and introduce physical activity and mindfulness based approaches as coping mechanisms to mothers of stillborn babies.
Methods: This was an exploratory qualitative research study. Participants were African American, Hispanic, Asian, and American Indian women, between the ages of 26 and 38, who have experienced stillbirth within the past 3 years. Participants completed a 20-30 minute phone interview.
Results: Fourteen women participated in the study (M age = 31.02 ± 5.97 years; M time since stillbirth = 1.47 ± 0.94 years). Women’s perceptions about physical activity and mindfulness to cope with grief were coded into the following major themes: perception of health care after stillbirth (satisfaction with the level of care provided), recommendations about inter-conception health care from physician (relating to mental, emotional, and physical health), grief (comfort with communicating with the physician), coping mechanisms, perception of the relationship between physical activity and mood, barriers to participating in physical activity (social and behavioral), pre-pregnancy physical activity, and perception of mindful approach (e.g., yoga) as a coping mechanism.
Conclusion: This was the first study to explore perceptions of health care and the use of physical activity and/or mindful approaches (e.g., yoga) to cope with grief after stillbirth in women of racial/ethnic minority. Findings from this study may help inform health care professionals alter their care practices and introduce physical activity and mindfulness based approaches as coping mechanisms to mothers of stillborn babies.
ContributorsArvayo, Jordan Michelle (Author) / Huberty, Jennifer (Thesis director) / Hoffner, Kristin (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2015-05
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Description
This study examined the effect of an 8-week exercise intervention on functional exercise capacity in adolescents with Down syndrome (DS). Forty participants were randomly assigned to one of three groups: assisted cycling (ACT) (n = 17) where participants experienced at least a 35% increase in their voluntary cycling speed through the use of a motor, voluntary cycling (VC) (n = 15) where participants cycled at a self-selected cadence, and no cycling (NC) (n = 8) where participants did not participate in any cycling intervention. In each cycling intervention, each participant completed three, 30 minute cycling sessions per week for a total of eight weeks. The Six-Minute Walk Test (6MWT) was administered prior to and after the 8-week intervention in pre-test and post-test assessment sessions, respectively. Our hypothesis was somewhat supported in that functional exercise capacity improved after ACT as measured by an increase in total number of laps walked, total distance walked, and average walking speed during the 6MWT, when compared to VC or NC.
ContributorsCook, Megan Rey (Author) / Ringenbach, Shannon (Thesis director) / Huberty, Jennifer (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2015-05
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Description
Objective: Fewer than 50% of female college freshmen meet physical activity (PA) guidelines. Innovative approaches that help college women increase their PA are warranted. The study purpose was to pilot test a magazine-based discussion group for improving PA, self-worth, and nutrition behaviors in freshmen college females. Method: Thirty-seven women (18-20 years) were randomized to intervention (n=17) and control (n=20) groups. The intervention group participated in an 8-week magazine-based discussion group adapted from a previously tested social cognitive theory based intervention, Fit Minded. Excerpts from a popular women's health magazine were discussed during weekly meetings incorporating PA, self-worth and nutrition education. The control group did not attend meetings, but received the magazines. Outcomes and feasibility measures included: self-reported PA, general self-worth, knowledge self-worth, self-efficacy, social support, and daily fruits, vegetables, junk food, sugar-sweetened beverage consumption. Results: Twelve participants from the intervention group attended more than 75% of meetings. A time effect was observed for PA (p=0.001) and family social support (p=0.002). Time x group effects were observed for PA (p=0.001), general self-worth (p=0.04), knowledge self-worth (p=0.03), and daily sugar-sweetened beverage consumption (p=0.03), with the intervention group reporting greater increases in PA, general self-worth and knowledge self-worth and greater decreases in daily sugar-sweetened beverage consumption. Although not significant, the intervention group demonstrated positive trends in self-efficacy, friend social support and fruit and veggie consumption as compared to the control group. Conclusion: A magazine-based discussion group may provide a promising platform to improve PA, self-worth and nutrition behaviors in female college freshmen.
ContributorsPellitteri, Katelyn (Author) / Huberty, Jennifer (Thesis director) / Bruening, Meg (Committee member) / Barrett, The Honors College (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor) / School of Social Transformation (Contributor) / Sandra Day O'Connor College of Law (Contributor)
Created2014-05
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Description
DNA methylation, a subset of epigenetics, has been found to be a significant marker associated with variations in gene expression and activity across the entire human genome. As of now, however, there is little to no information about how DNA methylation varies between different tissues inside a singular person's body. By using research data from a preliminary study of lean and obese clinical subjects, this study attempts to put together a profile of the differences in DNA methylation that can be observed between two particular body tissues from this subject group: blood and skeletal muscle. This study allows us to start describing the changes that occur at the epigenetic level that influence how differently these two tissues operate, along with seeing how these tissues change between individuals of different weight classes, especially in the context of the development of symptoms of Type 2 Diabetes.
ContributorsRappazzo, Micah Gabriel (Author) / Coletta, Dawn (Thesis director) / Katsanos, Christos (Committee member) / Dinu, Valentin (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / Department of Psychology (Contributor)
Created2013-12