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An algorithm for detecting features of the hormone profiles of the human menstrual cycle.
Krieg-EF Jr.; Kesner-JS; Knecht-EA
Comput Biol Med 1999 Jul; 29(4):229-242
An algorithm for detecting features of the cycles of the gonadotropic and ovarian hormones in women is described. The algorithm can detect hormone peaks and normal cycles defined in terms of the peaks in sequences of measurements that have an arbitrary starting point in the menstrual cycle and are of arbitrary length. The algorithm makes use of fuzzy set theory and is optimized using signal detection theory.
Mathematical-models; Reproductive-system; Women; Hormone-activity; Hormones; Gonadotropic-hormones; Biological-rhythms; Humans; Author Keywords: Algorithm; Fuzzy set; Signal detection; Menstrual cycle; Hormone
Edward F. Krieg Jr, National Institute for Occupational Safety and Health, 4676 Columbia Parkway, Cincinnati, OH 45226, USA
Issue of Publication
Computers in Biology and Medicine
Page last reviewed: April 12, 2019
Content source: National Institute for Occupational Safety and Health Education and Information Division