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We illustrate the use of machine learning techniques to analyze, structure, maintain, and evolve a large online corpus of academic literature. An emerging field of research can be identified as part of an existing corpus, permitting the implementation of a more coherent community structure for its practitioners.
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The success or otherwise of a radiographic examination is like other health-related interventions, crucially dependent upon the knowledge base of the radiographer and the quality of his/her clinical acumen. Traditional curricular approaches are limited in their ability to assist students to make vital connections between science and clinical decision making. This paper describes a computer-based case-oriented program called SOLAR (student oriented learning about radiography) that has been designed to achieve the necessary level of integration. The key feature of SOLAR is the requirement for students to construct a clinical action plan in response to a scenario provided. Upon submitting this plan, the student can then compare his/her plan to that prepared by an expert. The browsing configuration of SOLAR makes it highly attractive for other health professions as well. Student feedback indicates a high degree of approval for this approach.
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As science and technology become more sophisticated and with the rapid computation capabilities of the modern computer available, it becomes both possible and economically feasible to scientifically study man and his interaction with his working environment. It is now possible for a person seeking employment to expect and obtain a position which will not be unnecessarily hazardous to his immediate health or have detrimental effects over the long run. Manual materials handling is the contributor of over 400,000 back injuries suffered in the U.S. each year. This research is directed at determining the appropriate operator variables to measure for predicting the permissible weight of lift for three ranges of lift: floor to knuckle height, knuckle height to shoulder height, and shoulder height to reach height. A modified psychophysical procedure was used during which the subjects were instructed to adjust the weight in a tote box to the maximum weight they could lift repetitively without excessive strain or fatique. The task consisted of lifting loads under different conditions of task variables, namely, height of lift, frequency of lift, and load size. Industrial workers as well as students of both sexes were used as subjects. Based on the data obtained, the lifting capacity of the worker was determined for the different ranges of lift. In addition, predictive models were developed based on the operator variables and the task variables investigated.
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PDB-REPRDB is a database of representative protein chains from the Protein Data Bank (PDB). Started at the Real World Computing Partnership (RWCP) in August 1997, it developed to the present system of PDB-REPRDB. In April 2001, the system was moved to the Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST) (http://www.cbrc.jp/); it is available at http://www.cbrc.jp/pdbreprdb/. The current database includes 33 368 protein chains from 16 682 PDB entries (1 September, 2002), from which are excluded (a) DNA and RNA data, (b) theoretically modeled data, (c) short chains (1<40 residues), or (d) data with non-standard amino acid residues at all residues. The number of entries including membrane protein structures in the PDB has increased rapidly with determination of numbers of membrane protein structures because of improved X-ray crystallography, NMR, and electron microscopic experimental techniques. Since many protein structure studies must address globular and membrane proteins separately, this new elimination factor, which excludes membrane protein chains, is introduced in the PDB-REPRDB system. Moreover, the PDB-REPRDB system for membrane protein chains begins at the same URL. The current membrane database includes 551 protein chains, including membrane domains in the SCOP database of release 1.59 (15 May, 2002).
PURPOSE: To evaluate preoptometry and optometry school grade point averages and Optometry Admission Test (OAT) scores as predictors of performance on the National Board of Examiners in Optometry NBEO Part I (Basic Science) (NBEOPI) examination. METHODS: Simple and multiple correlation coefficients were computed from data obtained from a sample of three consecutive classes of optometry students (1995-1997; n = 278) at Southern California College of Optometry. RESULTS: The GPA after year two of optometry school was the highest correlation (r = 0.75) among all predictor variables; the average of all scores on the OAT was the highest correlation among preoptometry predictor variables (r = 0.46). Stepwise regression analysis indicated a combination of the optometry GPA, the OAT Academic Average, and the GPA in certain optometry curricular tracks resulted in an improved correlation (multiple r = 0.81). Predicted NBEOPI scores were computed from the regression equation and then analyzed by receiver operating characteristic (roc) and statistic of agreement (kappa) methods. From this analysis, we identified the predicted score that maximized identification of true and false NBEOPI failures (71% and 10%, respectively). Cross validation of this result on a separate class of optometry students resulted in a slightly lower correlation between actual and predicted NBEOPI scores (r = 0.77) but showed the criterion-predicted score to be somewhat lax. CONCLUSIONS: The optometry school GPA after 2 years is a reasonably good predictor of performance on the full NBEOPI examination, but the prediction is enhanced by adding the Academic Average OAT score. However, predicting performance in certain subject areas of the NBEOPI examination, for example Psychology and Ocular/Visual Biology, was rather insubstantial. Nevertheless, predicting NBEOPI performance from the best combination of year two optometry GPAs and preoptometry variables is better than has been shown in previous studies predicting optometry GPA from the best combination of preoptometry variables.
Healthy physiological systems exhibit marked signal variability and complexity, whereas diseased systems generally show a loss of variability, decreased complexity ("decomplexification"), and increased regularity. The goal of this study was to evaluate the uncoupling and recoupling phenomenon in children with septic shock by observing serial changes in heart rate variability metrics. Data were collected from 7 children with septic shock by using the computer system in the Complex Systems Laboratory at Oregon Health Sciences University. Heart rate time series were constructed and analyzed by using the Hales Research System at intervals of 6 h during pediatric intensive care unit (PICU) hospitalization. These power spectral values were then plotted vs. time. Six of seven patients showed an increase over time in low-frequency heart rate power and the low-/high-frequency ratio, whereas high-frequency heart rate power decreased. We also compared the change in mean heart rate, heart rate standard deviation, and power spectral values during the first 24 h of PICU hospitalization vs. the remainder of the PICU stay (for the 5 patients with a PICU length of stay > 48 h). Compared to the initial 24 h in the PICU, low-frequency power and the low-/high-frequency ratio increased, whereas high-frequency power decreased over the course of the illness. This report shows the potential value of monitoring the uncoupling and recoupling phenomenon in patients with septic shock. Our results are in agreement with other investigators who report evidence of decomplexification both in experimental models of sepsis and in clinical studies and provide direction for further work.
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We describe the service architecture of the successful TeraGyroid experiment. In particular we discuss the use of the open Grid service infrastructure (OGSI) to build the services used during the experiment and illustrate the problems we encountered.
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Modern science is preoccupied with basic mechanisms at the level of the gene, molecule, atom and fundamental particle. This preoccupation has affected attitudes to medical science. Paradoxically, politicians and Departments of Health are largely concerned with clinical epiphenomena--outcomes, interventions, effectiveness, efficiency--that are often disregarded by medical scientists and viewed without favour by granting bodies. In the surgical sciences, there is renewed interest in clinical research. The small computer and the readily available database with its compatible statistical package have added a new dimension to clinical research. Database design and analysis are as much a part of the surgical investigator's skills as are laboratory techniques. There are simple rules that govern database design. The database should be simple and flexible, but provide an adequate patient profile. Entry should be standardized by precise inclusion criteria and precise definitions. Data input should be numerical whenever possible. The database program should convert simply to a comprehensive statistical program. The clinical database is useful for both observational and investigational studies. Case series, case control studies and cohort studies can all be developed from well maintained databases. In the Department of Surgery at Westmead Hospital, databases have been maintained for 10 years. The hepatobiliary and pancreatic group of databases have led to 34 publications. The liver tumour database has produced 12 studies and nearly 20 papers. The process of development of one study is outlined in detail. The chance observation of an excess incidence of gallstones in patients having regular ultrasound examinations after major abdominal surgery has been confirmed in a case control study.(ABSTRACT TRUNCATED AT 250 WORDS)
Galileo wrote that "the book of nature is written in the language of mathematics"; his quantitative approach to understanding the natural world arguably marks the beginning of modern science. Nearly 400 years later, the fragmented teaching of science in our universities still leaves biology outside the quantitative and mathematical culture that has come to define the physical sciences and engineering. This strikes us as particularly inopportune at a time when opportunities for quantitative thinking about biological systems are exploding. We propose that a way out of this dilemma is a unified introductory science curriculum that fully incorporates mathematics and quantitative thinking.
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