Journal ArticleDOI
Bayesian classification for the selection of in vitro human embryos using morphological and clinical data
Dinora A. Morales,Endika Bengoetxea,Pedro Larrañaga,M. A. García,Yosu Franco,Mónica Fresnada,Marisa Merino +6 more
TLDR
An intelligent decision support system based on supervised classification by Bayesian classifiers to aid to the selection of the most promising embryos that will form the batch to be transferred to the woman's uterus is proposed.About:
This article is published in Computer Methods and Programs in Biomedicine.The article was published on 2008-05-01. It has received 64 citations till now. The article focuses on the topics: Naive Bayes classifier.read more
Citations
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Journal ArticleDOI
Artificial intelligence techniques for embryo and oocyte classification.
TL;DR: The proposed artificial intelligence system is based on a set of Levenberg-Marquardt neural networks trained using textural descriptors (the local binary patterns') and shows an interesting classification performance.
Journal ArticleDOI
A Review on Automatic Analysis of Human Embryo Microscope Images
TL;DR: The main embryo scoring systems currently in use are described and related works on embryo image analysis that could lead to an automatic and precise grading of embryo quality are reviewed.
Journal ArticleDOI
Artificial intelligence in reproductive medicine
Renjie Wang,Wei Pan,Lei Jin,Yuehan Li,Yudi Geng,Chun Gao,Gang Chen,Hui Wang,Ding Ma,Shujie Liao +9 more
TL;DR: The basic aspects of AI and machine learning are discussed, the applications, potential limitations and challenges of AI are addressed, and the prospects and future directions in the context of reproductive medicine are highlighted.
Journal ArticleDOI
Predictive Modeling of Implantation Outcome in an In Vitro Fertilization Setting An Application of Machine Learning Methods
TL;DR: A machine learning–based decision support system would be useful in improving the success rates of IVF treatment, with higher accuracy compared with expert judgment alone.
Journal ArticleDOI
A machine learning approach for prediction of pregnancy outcome following IVF treatment
TL;DR: A hill climbing feature (attribute) selection algorithm coupled with automated classification using machine learning techniques with the aim to analyze and predict IVF pregnancy in greater accuracy is proposed.
References
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Elements of information theory
Thomas M. Cover,Joy A. Thomas +1 more
TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
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Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
TL;DR: Probabilistic Reasoning in Intelligent Systems as mentioned in this paper is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty, and provides a coherent explication of probability as a language for reasoning with partial belief.
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Pattern Classification and Scene Analysis.
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Pattern classification and scene analysis
Richard O. Duda,Peter E. Hart +1 more
TL;DR: In this article, a unified, comprehensive and up-to-date treatment of both statistical and descriptive methods for pattern recognition is provided, including Bayesian decision theory, supervised and unsupervised learning, nonparametric techniques, discriminant analysis, clustering, preprosessing of pictorial data, spatial filtering, shape description techniques, perspective transformations, projective invariants, linguistic procedures, and artificial intelligence techniques for scene analysis.