How to locate educational information and data; an aid to quick utilization of the literature of education

Mode of access: Internet.

Pioneer settlement in the Asiatic tropics; studies in land utilization and agricultural colonization in southeastern Asia

"This study has been made with the cooperation of the Secretariat of the Institute of Pacific relations and constitutes a report in its International research series."

Lodgepole pine commercial forests : an essay comparing the natural cycle of insect kill and subsequent wildfire with management for utilization and wildlife /

"September 1996."

The National Committee on Wood Utilization: Its Accomplishments and Aims

Mode of access: Internet.

National Medical Care Utilization and Expenditure Survey.

Title from cover.

Land utilization and rural economy in Korea,

Mode of access: Internet.

Characterizing Healthcare Utilization, Direct Costs, and Comorbidities Associated with Interstitial Cystitis: A Retrospective Claims Analysis

Thesis (Master's)--University of Washington, 2016-06

Racial Disparities in the Utilization of Preventive Health Services among Older Women with Early Stage Endometrial Cancer Enrolled in Medicare

Thesis (Master's)--University of Washington, 2016-06

Wading through the quagmire: Making sense of dietary supplement utilization

Since the 1980s, numerous studies conducted in the United States have attempted to estimate the prevalence of supplement use among the population (e.g., the National Health and Nutrition Survey and the National Health Interview Surveys). Despite these efforts, the true extent of supplement use is unclear. The literature pertaining to the prevalence of supplement use refers to a confusing array of ambiguous terms. Forming accurate conclusions about supplement use is confounded by differences in terminology and methodology between studies. Direct comparisons between studies are therefore inherently problematic. The emphasis in future investigations should be on standardizing the study design; recording data on daily, weekly, or even monthly use in order to establish the safety and efficacy of supplement use; and adopting a consistent, uniform definition of the term supplement.

An Incremental EM-based Learning Approach for On-Line Prediction of Hospital Resource Utilization

Objective: Inpatient length of stay (LOS) is an important measure of hospital activity, health care resource consumption, and patient acuity. This research work aims at developing an incremental expectation maximization (EM) based learning approach on mixture of experts (ME) system for on-line prediction of LOS. The use of a batchmode learning process in most existing artificial neural networks to predict LOS is unrealistic, as the data become available over time and their pattern change dynamically. In contrast, an on-line process is capable of providing an output whenever a new datum becomes available. This on-the-spot information is therefore more useful and practical for making decisions, especially when one deals with a tremendous amount of data. Methods and material: The proposed approach is illustrated using a real example of gastroenteritis LOS data. The data set was extracted from a retrospective cohort study on all infants born in 1995-1997 and their subsequent admissions for gastroenteritis. The total number of admissions in this data set was n = 692. Linked hospitalization records of the cohort were retrieved retrospectively to derive the outcome measure, patient demographics, and associated co-morbidities information. A comparative study of the incremental learning and the batch-mode learning algorithms is considered. The performances of the learning algorithms are compared based on the mean absolute difference (MAD) between the predictions and the actual LOS, and the proportion of predictions with MAD < 1 day (Prop(MAD < 1)). The significance of the comparison is assessed through a regression analysis. Results: The incremental learning algorithm provides better on-line prediction of LOS when the system has gained sufficient training from more examples (MAD = 1.77 days and Prop(MAD < 1) = 54.3%), compared to that using the batch-mode learning. The regression analysis indicates a significant decrease of MAD (p-value = 0.063) and a significant (p-value = 0.044) increase of Prop(MAD