✦ LIBER ✦

Comparing data mining and logistic regression for predicting IVF outcome

✍ Scribed by James R. Trimarchi; Julie Goodside; Leah Passmore; Tali Silberstein; Lutz Hamel; Liliana Gonzalez

Book ID: 119421398
Publisher: Elsevier Science
Year: 2003
Tongue: English
Weight: 46 KB
Volume: 80
Category: Article
ISSN: 1556-5653
DOI: 10.1016/s0015-0282(03)02065-x

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

OC041: Pregnancies of unknown location:

OC041: Pregnancies of unknown location: a new logistic regression model for predicting outcome

✍ E. Kirk; G. Condous; A. Khalid; Z. Haider; N. Rosello; C. Lu; T. Bourne 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 37 KB

Advantages and disadvantages of using ar

Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes

✍ Jack V. Tu 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 946 KB

Comparing discriminant analysis, neural

Comparing discriminant analysis, neural networks and logistic regression for predicting species distributions: a case study with a Himalayan river bird

✍ Stéphanie Manel; Jean-Marie Dias; Steve J. Ormerod 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 128 KB

Artificial neural networks for the predi

Artificial neural networks for the prediction of IVF outcome using clinical and morphological data

✍ G.A. Bello; M.G. Rodríguez; M.T. Olivieri; E.H. Rosemberg; S. Bronfenmajer 📂 Article 📅 2010 🏛 Elsevier Science 🌐 English ⚖ 37 KB

Comparing performances of logistic regre

Comparing performances of logistic regression and neural networks for predicting melatonin excretion patterns in the rat exposed to ELF magnetic fields

✍ Samad Jahandideh; Parviz Abdolmaleki; Mohammad Mehdi Movahedi 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 94 KB 👁 1 views

## Abstract Various studies have been reported on the bioeffects of magnetic field exposure; however, no consensus or guideline is available for experimental designs relating to exposure conditions as yet. In this study, logistic regression (LR) and artificial neural networks (ANNs) were used in or

Logistic regression models for predictin

Logistic regression models for predicting occurrence of terrestrial molluscs in southern Sweden – importance of environmental data quality and model complexity

✍ Åke Berg; Ulf Gärdenfors; Ted Von Proschwitz 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 279 KB