R. Galen and S. Gambino. Beyond Normality: The Predictive Value and Efficiency of Medical Diagnoses. John Wiley & Sons, New York, 1975. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Predicting Defects in Disk Drive Manufacturing: A Case.. - Apte, Weiss, Grout (1993) (1 citation) (Correct)
....presence in the rule set. Fields 595 through 608 have been identified as the key fields. We also hypothesized an artificial test that is a derivative of other tests: the numberofthesekey fields that haveavalue of 0.05 or more. Analogous to rule induction techniques for medical diagnostic testing [5], we considered thresholding these tests to determine the predictivevalue at eachnumerical cutoff, a process known as referentvalue analysis. In purely symbolic terms a single best rule has been induced in the following form: If 5 or more fields in 595 608 are 0:05 OR There exists a field in ....
R. Galen and S. Gambino. Beyond Normality: The Predictive Value and Efficiency of Medical Diagnoses. John Wiley & Sons, New York, 1975.
Case Studies in High-Dimensional Classification - Apte, Sasisekharan, Seshadri, .. (1994) (Correct)
....Sample 0.50 0.859 0.831 0.75 0.913 0.860 1.00 0.950 0.862 1.25 0.945 0.856 1.50 0.956 0.877 1.75 0.944 0.893 Table 2: PredictiveValue Analysis other tests: the number of these key fields that haveavalue of 0.05 or more. Analogous to rule induction techniques for medical diagnostic testing [5], we considered thresholding these tests to determine the predictivevalue at eachnumerical cutoff, a process known as referentvalue analysis. In purely symbolic terms a single best rule has been induced in the following form: If 5 or more fields in 595 608 are 0:05 OR There exists a field in ....
R. Galen and S. Gambino. Beyond Normality: The Predictive Value and Efficiency of Medical Diagnoses. John Wiley & Sons, New York, 1975.
Use of a Multi-Layer Perceptron to Predict.. - Verrelst, Moreau, .. (1997) (2 citations) (Correct)
....cases. Receiver Operating Characteristic (ROC) curves are a way to visualize this relationship. The plot gives the sensitivity versus false positive rate for varying thresholds T (e.g. Figure 2) The ROC curve is useful and widely used device for assessing and comparing the value of tests [5, 7]. The proportion of the whole area of the graph which lies below the ROC curve is a one value measure of the accuracy of a test [6] The higher this proportion, the better the test. Figure 2 shows the ROC curves for two simple classifiers that use only one single indicator. Which means that we ....
Galen R.S., Gambino S., Beyond normality: the predictive value and efficiency of medical diagnosis, John Wiley, New York, 1975.
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