scholarly journals Purpose of Nutrient Data Banks and Options for Eurofoods

1985 ◽  
Vol 29 (1) ◽  
pp. 9-10
Keyword(s):  
Nutrient Data ◽  
Data Banks

Determining the Most Valuable Clinical Variables : a Stepwise Multiple Logistic Regression Program

1980 ◽  
Vol 19 (01) ◽  
pp. 42-49 ◽  
Author(s):  
B. W. Brown ◽  
C. Engelhard ◽  
J. Haipern ◽  
J. F. Fries ◽  
L. S. Coles
Keyword(s):  
Logistic Regression ◽  
Predictor Variable ◽  
Clinical Problem ◽  
Relevant Information ◽  
Stepwise Logistic Regression ◽  
Multiple Logistic Regression ◽  
Binary Outcome ◽  
Medical Problems ◽  
Valuable Predictor ◽  
Data Banks

In solving a clinical problem of diagnosis, prognosis, or treatment choice, a physician must select from among a large group of possible tests. In general, an ordering exists specifying which tests are most valuable in providing relevant information concerning the problem on hand. The computer program package to be described (MW) extracts appropriate data from the ARAMIS data banks and then analyzes the data by stepwise logistic regression. A binary outcome (diagnosis, prognostic event, or treatment response) is sequentially associated with possible tests, and the most powerful combination of tests is identified. For example, the most valuable predictor variable of early mortality in SLE is proteinuria, followed sequentially by anemia and absence of arthritis. Experience with these techniques suggests : 1. optimal certainty is usually reached after only three or four tests; 2. several different test sequences may lead to the same level of certainty; 3. diagnosis may usually be ascertained with greater certainty than prognosis; 4. many medical problems contain considerable non-reducible uncertainty; 5. a relatively small group of tests are typically found among the most powerful; 6. results are consistent across several patient populations; 7. results are largely independent of the particular statistic employed. These observations suggest strategies for maximizing information while minimizing risk and expense.

Chemical toxicology searching: a collaborative evaluation, comparing information resources and searching techniques

1982 ◽  
Vol 5 (1) ◽  
pp. 3-18 ◽  
Author(s):  
David Bawden ◽  
Alison M. Brock
Keyword(s):  
Public Sector ◽  
Failure Analysis ◽  
Objective Evaluation ◽  
Information Resources ◽  
Data Bases ◽  
Online Data ◽  
Chemical Toxicology ◽  
Collaborative Evaluation ◽  
Evaluation Project ◽  
Data Banks

A collaborative evaluation project has been carried out by fourteen UK and European organisations, both industrial and public sector, to compare information resources and searching techniques for chemical toxrcology information. The project had two objectives: to improve the participants' own expertise in this area, and to allow an objective evaluation of searching methods. Eight test queries were designed and searched by the participants, and the results evaluated semi-qualitatively, with an extensive failure analysis. Printed sources, online data-bases, data-banks, and in-house files were included in the evaluation. The results are presented and discussed, including both comments on strengths and weaknesses of sources and search techniques, and recommenda tions for future improvements to facilitate access to chemical toxicology information.

scholarly journals Linguistic Data Banks and the Technical Translator

1971 ◽  
Vol 16 (1-2) ◽  
pp. 117 ◽  
Author(s):  
Friedrich Krollmann
Keyword(s):  
Linguistic Data ◽  
Data Banks
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