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Deep Learning of Markov Model Based Machines for Determination of Better Treatment Option Decisions for Infertile Women

Arni S.R. Srinivasa Rao, Michael P. Diamond
doi: https://doi.org/10.1101/606921
Arni S.R. Srinivasa Rao
aLaboratory for Theory and Mathematical Modeling, Division of Infectious Diseases, Medical College of Georgia, Augusta University, USA. Address: 1120, 15th Street, Augusta, GA, 30912
bDivision of Epidemiology-Department of Population Health, Medical College of Georgia, Augusta University, USA
cDepartment of Mathematics, College of Science and Mathematics, Augusta University, USA
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  • For correspondence: arrao@augusta.edu
Michael P. Diamond
dDepartment of Obstetrics and Gynecology, Medical College of Georgia, Augusta University, USA. Address: 1120, 15th Street, CJ-1306, Augusta, GA, 30912
eSenior Vice President, Office of Senior Vice President, Augusta University, USA
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Abstract

In this technical article, we are proposing ideas those we have been developing of how machine learning and deep learning techniques can potentially assist obstetricians / gynecologists in better clinical decision making using infertile women in their treatment options in combination with mathematical modeling in pregnant women as examples.

Footnotes

  • Email: midiamond{at}augusta.edu

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 12, 2019.
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Deep Learning of Markov Model Based Machines for Determination of Better Treatment Option Decisions for Infertile Women
Arni S.R. Srinivasa Rao, Michael P. Diamond
bioRxiv 606921; doi: https://doi.org/10.1101/606921
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Deep Learning of Markov Model Based Machines for Determination of Better Treatment Option Decisions for Infertile Women
Arni S.R. Srinivasa Rao, Michael P. Diamond
bioRxiv 606921; doi: https://doi.org/10.1101/606921

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