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Sensitivity and Specificity Improvement in Abdominal Obesity Diagnosis Using Cluster Analysis during Waist Circumference Cut-Off Point Selection.

Valmore BermúdezJoselyn RojasJuan SalazarRoberto AñezAlexandra ToledoLuis BelloVanessa ApruzzeseRobys GonzálezMaricarmen ChacínMayela CabreraClímaco CanoManuel VelascoJosé López-Miranda
Published in: Journal of diabetes research (2015)
TSCA in the selection of the groups used in ROC curves construction proved to be an important tool, aiding in the detection of MOWN and MHO which cannot be identified with WC alone. The resulting WC cutpoints were <91.00 cm for women and <98.00 cm for men. Furthermore, anthropometry is insufficient to determine healthiness, and, biochemical analysis is needed to properly filter subjects during classification.
Keyphrases
  • body mass index
  • machine learning
  • metabolic syndrome
  • deep learning
  • polycystic ovary syndrome
  • physical activity
  • pregnant women
  • skeletal muscle
  • real time pcr