A study of assess the effectiveness of a structured cardiac rehabilitation programme on knowledge regarding self-care activities, quality of life, stress and coping among patients undergoing cardiac surgery at selected hospital of Bangalore
M.Sc. (Tech) Rafael Savvides defends his doctoral thesis "Statistical methods for testing visual patterns, selecting models, and bounding model errors " on Friday the 11th of October 2024 at 13 o'clock in the University of Helsinki Exactum building, Auditorium CK112 (Pietari Kalmin katu 5, basement). His opponent is Professor Pauli Miettinen (University of Eastern Finland) and custos Professor Kai Puolamäki (University of Helsinki). The defence will be held in English.
The thesis of Rafael Savvides is a part of research done in the Department of Computer Science and in the Exploratory Data Analysis group at the University of Helsinki. His supervisor has been Professor Kai Puolamäki (University of Helsinki).
Data science involves data analysis and building models on data. The analyses and the models produced by data scientists are used for making decisions and for creating products that affect our lives. However, real world data are imperfect, which introduces uncertainties into analyses and models based on data. The uncertainties propagate to down-stream decisions and products, which can be negatively affected if these uncertainties are not made explicit.
This thesis introduces three computational methods that aid with uncertainties when analyzing data and building models based on data. The methods provide formal statistical guarantees about visual patterns in data exploration, models selected based on their expected errors in model selection, and model errors on specific data points. The methods concern fundamental problems in machine learning and therefore have wide applicability.
The first method concerns patterns observed during data exploration. Data scientists typically explore data using various visualizations that reveal patterns in the data. Since data are noisy, the observed visual patterns may also be due to noise, rather than a true effect in the data. Determining whether something is a true pattern or a random occurrence is traditionally determined using statistical testing. The method we developed is a statistical testing procedure for testing visual patterns during visual data exploration. The procedure allows analysts to measure whether what they see is compatible with their accumulated knowledge of the data.
The second method concerns selecting between machine learning models. When faced with a prediction task, data scientists use data to train and validate multiple models. In the end, only one model will be used, which is selected based on some criterion. The criterion usually relates to the average error on new data, which is estimated using data not seen during training. However, it is not clear how much new data should be used to estimate the performance; more data is always better, but there is a finite amount for both training models and validating them. Using less data leads to a more uncertain selection, but it is not clear how to quantify that uncertainty. The method we developed is a model selection algorithm that automatically decides how much data to use for selecting between models. The algorithm uses as much data as required to ensure a formal confidence guarantee that the selected model's loss is within a specified tolerance from the best model.
The third method concerns estimating prediction errors on specific data points. The performance of a machine learning model is typically evaluated using an average prediction error. However, since the model predicts on individual points, it can often be more important to estimate the (unknown) error at a specific test point, which can differ significantly from the average error. The method we developed provides an upper bound for the prediction error of any regression model at a given test point. The bound is based on a powerful model for quantifying uncertainties given by Gaussian processes. The bound improves upon existing methods based on Gaussian processes by requiring less information from the user, being applicable to a large class of kernels and any regressor, and being computationally faster.
An electronic version of the doctoral dissertation will be available in the University of Helsinki open repository Helda at http://urn.fi/URN:ISBN:978-952-84-0695-2 .
Printed copies will be available on request from Rafael Savvides: [email protected]
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Theses/Dissertations from 2019. PDF. Perceived Discrimination and Cardiovascular Outcomes in Blacks: A Secondary Data Analysis of the Heart SCORE Study, Marilyn Aluoch. PDF. Exploration of Gratitude in Cardiovascular Health: Mediators, Medication Adherence and Psychometrics, Lakeshia A. Cousin.
Follow. Theses/Dissertations from 2021 PDF. Effectiveness of Comprehensive Hemophilia Education Program (CHEP) on health related Quality of Life and Clinical outcomes of children and young people with hemophilia in selected hemophila clinics of Karnataka., Anjalin D'Souza PDF
Theses/Dissertations from 2021. PDF. Early Premature Infant Physiologic and Behavioral Indicators of ANS Instability, Karen Popp Becker. PDF. Nurses' and Patients' Perceptions of the Availability of Post-hospital Instrumental Support as a Predictor of 30- And 60-Day Acute Care Utilization, Beth E. Schultz. PDF.
Theses/Dissertations from 2023. PDF. Why We Work: Exploring the Relationships Between Work Rewards, Burnout, and Intention to Leave for Professional Nurses, Jacqueline Christianson. PDF. Examining Relationships Among Nursing Students' Views of Suffering, Positive Thinking, and Professional Quality of Life, Ruth Anne Engbers. PDF.
Yale School of Nursing Digital Theses. Starting with the Yale School of Nursing (YSN) graduating class of 2012, students who completed a master's thesis have submitted it to the ProQuest Dissertations and Thesis database. Additionally in 2014 the YSN Doctor of Nursing Practice program (DNP) have submitted their final capstone project to ProQuest.
Nursing School Theses, Dissertations, and Doctoral Papers. The Relationship Between Instrumental Activities of Daily Living and Hospitalizations: A Systematic Review and Meta-Analysis. Instrumental activities of daily living (IADL) have been defined as the activities for which their performance is necessary for continued independent living ...
Theses/Dissertations from 2023. PDF. THE PERCEPTIONS OF PEOPLE WITH DEMENTIA, CARE PARTNERS, CNAs/SITTERS, AND PROVIDERS DURING THE COVID-19 PANDEMIC UP TO NOW: A MULTIPLE CASE STUDY, Gaudensia Awuor. PDF. Commitment to Collaboration: Development of a School Nursing Collaboration Instrument, Jodi S. Bullard. PDF.
theses/dissertations from 2020 pdf. tobacco use and nicotine withdrawal among patients with mental illness, yazan daher al-mrayat. pdf. associations between psychosocial stressors, genes, and cardiovascular disease in at-risk adults, kaitlin voigts key. pdf. responses to symptoms among patients with heart failure, chin-yen lin. pdf
The dissertation focuses on the experience of professional nurses concerning their. preparation to teach nursing students in the clinical setting. The topic is important because a. clinical education is the primary source of real-life experience for nursing students (Romig, Maillet, Chute, & McLaughlin, 2013).
A study to assess the effectiveness of planned nursing interventions on health status of mechanically ventilated patients admitted in selected intensive care units of aurangabad: Deshmukh, Rahul R: Mhaske, Anuradha N: 14-Mar-2024: Develop and Evaluate Practice Model for caregivers in creches: Arunima S: Ponchitra R: 6-Dec-2023
Theses/Dissertations from 2022 PDF. Nurse Managers' Patient Safety Communication, Christine Deatrick. PDF. Exploration of the Oral Microbiome in Non-Ventilated Hospitalized Patients, Kimberly Emery. PDF. Social Support and Empowerment Among Caregivers of Children with Asthma, Lauren Lebo. Theses/Dissertations from 2021 PDF
Conclusion. This article has outlined some of the steps that a PhD student should consider in order to produce a high- quality thesis and ensure a successful viva. We have considered how it is important that decision- making. Table 2. Characteristics of a poor and excellent thesis6. Poor thesis. Lack of coherence.
Theses/Dissertations from 2020. Interprofessional Role Clarification Among Licensed Health Care Practitioners in Rural and Smaller Community Hospitals, Dianne E. Allen. Exploring Nursing Student Use of Instagram: Selfies and Soliloquies and #becominganurse with Evolving Digital Footprints, Kingsley KS Au.
Theses/Dissertations from 2010. PDF. The effect of exercise experience on imagery use, efficacy beliefs, and body image among females., Lisa M. Cooke. PDF. Exploring the psychometric properties of the newly-developed Undergraduate Nursing Student Academic Satisfaction Scale, Susan Dennison. PDF.
This Dissertation is brought to you for free and open access by the Walden Dissertations and Doctoral Studies Collection at ScholarWorks. It has been ... BSc (Hons) Nursing, Delhi University, 1990 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Health Management and Policy Walden University
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ScholarWorks at Georgia State University includes Doctoral Dissertations contributed by students of the Byrdine F. Lewis College of Nursing & Health Professions at Georgia State University. The institutional repository is administered by the Georgia State University Library in cooperation with individual departments and academic units of the University.
The Doctor of Philosophy (Ph.D.) in Nursing Dissertation Handbook guides students in the dissertation process according to the requirements of Wilkes University and the Passan School of Nursing. The handbook is divided into three parts: the Ph.D. in Nursing program and dissertation process, guidelines for writing the dissertation proposal and ...
This Doctoral Student and Dissertation Guide has been designed to guide students in the preparation of their candidacy and doctoral dissertations according to the requirements of Nova Southeastern University Health Professions Division College of Nursing, PhD in Nursing Education Program. The document describes the steps of candidacy and the ...
Christine E Lynn College of Nursing PhD in Nursing Program Outline Guide for Dissertation Quantitative Study Qualitative Study Chapter 1: Introduction • Phenomenon of interest • Problem statement • Purpose of the study • Significance of the study including connection to caring science • Research questions/hypotheses where
Candidate: Ana DiNatale Stoehr. Dissertation Chair: Dr. Marie Kodadek. Does the Type of Delivery and Hospital Practices Impact Breastfeeding Self-Efficacy and Outcomes at 10 Days and 8 Weeks Postpartum. Candidate: Candice Jean Sullivan. Dissertation Chair: Dr. Marie Kodadek. Explore innovative nursing research in GMU's Nursing PhD dissertations.
The core criteria for PhD success—ubiquitous to all disciplines and universities—are that the student; Produces a thesis is of sufficient rigour that the work is evaluated as publishable in relevant discipline-specific journal (s). Table 1 highlights some of the key ingredients of PhD success, in terms of the study, thesis and viva.
3. Name : Dr. Rakesh Patidar Email : [email protected] Topic : Health status of the children of a nation is a highly reliable index of the health of its population.School going children contribute around 40% of the population. School children aged 5-11 years suffer the highest infection rate and worm burden that attributes to poor sanitation and hygiene.
On the 11th of October 2024, M.Sc. (Tech) Rafael Savvides defends his PhD thesis on Statistical methods for uncertainties in data exploration and model building. The thesis is related to research done in the Department of Computer Science and the Exploratory Data Analysis group.