caa a22 4500 445308206 CHVBK 20180317142620.0 cr unu---uuuuu 170323e20110501xx s 000 0 eng 10.1007/s00404-010-1469-2 doi (NATIONALLICENCE)springer-10.1007/s00404-010-1469-2 Neural networks prediction of preterm delivery with first trimester bleeding [Elektronische Daten] [U. Elaveyini, S. Devi, K. Rao] Objective: This paper illustrates a retrospective study of the outcome of those pregnancies that continued from an initial episode of bleeding in first trimester. Methods: Neural networks is used for the prediction of preterm delivery, using various inputs such as the age of women, gestational age when the bleeding occurred, duration of the bleeding days, amount of bleeding, number of episodes, presence or absence of hematoma and placentation position. Results: The success rate of prediction obtained using the feed forward backpropogation network is 70%. Hence, this model can be used to identify women at the risk of premature delivery for planning antenatal care and clinical interventions in pregnancy. Springer-Verlag, 2010 First trimester bleeding nationallicence Preterm labor prediction nationallicence Neural networks nationallicence Elaveyini U. Department of Obstetrics and Gynecology, CSI Rainy Multispecialty Hospital, Chennai, India aut Devi S. Department of Industrial Engineering, Anna University, Chennai, India aut Rao K. Department of Industrial Engineering, Anna University, Chennai, India aut Archives of Gynecology and Obstetrics Springer-Verlag 283/5(2011-05-01), 971-979 0932-0067 283:5<971 2011 283 404 https://doi.org/10.1007/s00404-010-1469-2 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00404-010-1469-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Elaveyini U. Department of Obstetrics and Gynecology, CSI Rainy Multispecialty Hospital, Chennai, India aut NATIONALLICENCE 700 1- Devi S. Department of Industrial Engineering, Anna University, Chennai, India aut NATIONALLICENCE 700 1- Rao K. Department of Industrial Engineering, Anna University, Chennai, India aut NATIONALLICENCE 773 0- Archives of Gynecology and Obstetrics Springer-Verlag 283/5(2011-05-01), 971-979 0932-0067 283:5<971 2011 283 404 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer