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Estimating the chance of success in IVF treatment using a ranking algorithm

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Estimating the chance of success in IVF treatment using a ranking algorithm

Content Provider	Springer Nature Link
Author	Güvenir, H. Altay Misirli, Gizem Dilbaz, Serdar Ozdegirmenci, Ozlem Demir, Berfu Dilbaz, Berna
Copyright Year	2015
Abstract	In medicine, estimating the chance of success for treatment is important in deciding whether to begin the treatment or not. This paper focuses on the domain of in vitro fertilization (IVF), where estimating the outcome of a treatment is very crucial in the decision to proceed with treatment for both the clinicians and the infertile couples. IVF treatment is a stressful and costly process. It is very stressful for couples who want to have a baby. If an initial evaluation indicates a low pregnancy rate, decision of the couple may change not to start the IVF treatment. The aim of this study is twofold, firstly, to develop a technique that can be used to estimate the chance of success for a couple who wants to have a baby and secondly, to determine the attributes and their particular values affecting the outcome in IVF treatment. We propose a new technique, called success estimation using a ranking algorithm (SERA), for estimating the success of a treatment using a ranking-based algorithm. The particular ranking algorithm used here is RIMARC. The performance of the new algorithm is compared with two well-known algorithms that assign class probabilities to query instances. The algorithms used in the comparison are Naïve Bayes Classifier and Random Forest. The comparison is done in terms of area under the ROC curve, accuracy and execution time, using tenfold stratified cross-validation. The results indicate that the proposed SERA algorithm has a potential to be used successfully to estimate the probability of success in medical treatment.
Starting Page	911
Ending Page	920
Page Count	10
File Format	PDF
ISSN	01400118
Journal	Medical and Biological Engineering and Computing
Volume Number	53
Issue Number	9
e-ISSN	17410444
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-04-17
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Estimation of success Ranking Classification In vitro fertilization Clinical decision support system Human Physiology Biomedical Engineering Imaging Radiology Computer Applications
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering Computer Science Applications

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