Global ETD Search

21	Public health informatics : a consensus on core competencies / Richards, Janise Elaine, January 2000 (has links) Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 231-242). Available also in a digital version from Dissertation Abstracts.
22	Design, implementation and evalulation of the user interface for healthcare information systems in Hong Kong / Leung, Min-wing, Raymond. January 2001 (has links) Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 184-197).
23	A computer based data acquisition and analysis system for a cardiovascular research laboratory Suwarno, Neihl Omar, 1963- January 1989 (has links) No description available. Medical electronics. Medical informatics. Medicine -- Data processing.
24	Learning Accurate Regressors for Predicting Survival Times of Individual Cancer Patients Lin, Hsiu-Chin Unknown Date No description available. Survival Prediction Medical Informatics Machine Learning
25	Telemedicine and elderly care : an investigation into the suitability of an Internet health care system to support blood pressure monitoring for the older person; or telemedicine: one size fits all? Fitch, Christina Johanna January 2001 (has links) No description available. 658.05
26	Event calculus to support temporal reasoning in a clinical domain Abeysinghe, Geetha Kalyani January 1993 (has links) No description available. 003.5
27	Learning Accurate Regressors for Predicting Survival Times of Individual Cancer Patients Lin, Hsiu-Chin 06 1900 (has links) Standard survival analysis focuses on population-based studies. The objective of our work, survival prediction, is different: to find the most accurate model for predicting the survival times for each individual patient. We view this as a regression problem, where we try to map the features for each patient to his/her survival time. This is challenging in medical data due to the presence of irrelevant features, outliers, and missing class labels. Our approach consists of two major steps: (1) apply various grouping methods to segregate patients, and (2) apply different regression to each sub-group we obtained from the first step. We focus our experiments on a data set of 2402 patients (1260 censored). Our final predictor can obtain an average relative absolute error < 0.54. The experimental results verify that we can effectively predict survival times with a combination of statistical and machine learning approaches. Survival Prediction Medical Informatics Machine Learning
28	Improving chronic disease management in general practice medicine through Therapeutic State-Transition analysis / Gadzhanova, Svetla. Unknown Date (has links) With an aging population, chronic disease is rapidly becoming the major focus for the health care system as it affects the physical, emotional and mental well-being of individuals. Chronic disease management is a systematic approach offering real opportunities for improving the service quality for people with chronic disease. It can be delivered more effectively and efficiently if the providers are supported with knowledge-based resources and external expertise in the form of computer decision support. Increasing uptake of electronic medical records (EMRs) offers valuable opportunities for analysis and quality assurance of clinical practice; but making appropriate inferences about chronic disease management in non-trivial. / Thesis (PhD)--University of South Australia, 2006. Medical informatics. Disease management Medical records
29	LC sensor for biological tissue characterization / Yvanoff, Marie. January 2008 (has links) Thesis (Ph.D.)--Rochester Institute of Technology, 2008. / Typescript. Includes bibliographical references.
30	Use and acceptance of an electronic health record : factors affecting physician attitudes / Morton, Mary Elizabeth. Wiedenbeck, Susan. McCain, Katherine Wootton. January 2008 (has links) Thesis (Ph.D.)--Drexel University, 2008. / Includes abstract and vita. Includes bibliographical references (leaves 122-131).

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