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Predicting IVF outcome: a proposed web-based system using artificial intelligence

Abstract:

AIM: To propose a functional in vitro fertilization (IVF) prediction model to assist clinicians in tailoring personalized treatment of subfertile couples and improve assisted reproduction outcome. MATERIALS AND METHODS: Construction and evaluation of an enhanced web-based system with a novel Artificial Neural Network (ANN) architecture and conformed input and output parameters according to the clinical and bibliographical standards, driven by a complete data set and "trained" by a network exp...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MSD
Department:
NDORMS
Sub department:
Centre for Statistics in Medicine
Role:
Author
Publisher:
International Institute of Anticancer Research Publisher's website
Journal:
In Vivo Journal website
Volume:
30
Issue:
4
Pages:
507-512
Publication date:
2016-07-07
Acceptance date:
2016-04-02
EISSN:
1791-7549
ISSN:
0258-851X
Language:
English
Keywords:
Pubs id:
pubs:633928
UUID:
uuid:1a8dfead-4ca6-4d45-a7d2-3c744c4efa08
Local pid:
pubs:633928
Source identifiers:
633928
Deposit date:
2016-08-25

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