4.5 Article

Increasing sensitivity of preterm birth by changing rule strengths

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PATTERN RECOGNITION LETTERS
卷 24, 期 6, 页码 903-910

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ELSEVIER
DOI: 10.1016/S0167-8655(02)00202-7

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preterm birth; LERS system; data mining; rule induction; rough set theory

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We studied two prenatal data sets and two other medical data sets. Our objective was to increase sensitivity (accuracy of preterm birth) by changing the rule strength for the preterm birth class. Two criteria for choosing the optimal rule strength are discussed: the greatest difference between the true-positive and false-positive probabilities and the maximum profit. (C) 2002 Elsevier Science B.V. All rights reserved.

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