✦ LIBER ✦

Predicting the type of pregnancy using artificial neural networks and multinomial logistic regression: a comparison study

✍ Scribed by Seyed Mehdi Sadat-Hashemi; Anoshirvan Kazemnejad; Caro Lucas; Kambiz Badie

Publisher: Springer-Verlag
Year: 2004
Tongue: English
Weight: 264 KB
Volume: 14
Category: Article
ISSN: 0941-0643
DOI: 10.1007/s00521-004-0454-8

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Cropland change in southern Romania: a c

Cropland change in southern Romania: a comparison of logistic regressions and artificial neural networks

✍ Tobia Lakes; Daniel Müller; Carsten Krüger 📂 Article 📅 2009 🏛 Springer 🌐 English ⚖ 395 KB

Landslide susceptibility analysis and it

Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea

✍ Saro Lee; Joo-Hyung Ryu; Ii-Soo Kim 📂 Article 📅 2007 🏛 Springer 🌐 English ⚖ 777 KB

Comparison of the Levels of Accuracy of

Comparison of the Levels of Accuracy of an Artificial Neural Network Model and a Logistic Regression Model for the Diagnosis of Acute Appendicitis

✍ Shinya Sakai; Kuriko Kobayashi; Shin-ichi Toyabe; Nozomu Mandai; Tatsuo Kanda; K 📂 Article 📅 2007 🏛 Springer US 🌐 English ⚖ 149 KB

A comparison between functional networks

A comparison between functional networks and artificial neural networks for the prediction of fishing catches

✍ Alfonso Iglesias; Bernardino Arcay; J.M. Cotos; J.A. Taboada; Carlos Dafonte 📂 Article 📅 2004 🏛 Springer-Verlag 🌐 English ⚖ 414 KB

A comparison of ICU mortality prediction

A comparison of ICU mortality prediction using the APACHE II scoring system and artificial neural networks

✍ L. S. S. Wong; J. D. Young 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 229 KB

The aim of this study was to compare the ability of artificial neural networks and the Acute Physiology and Chronic Health Evaluation II score to predict mortality in adult intensive care units. The same physiological variables were used in both predictive models to predict hospital mortality from a

Landslide susceptibility mapping: A comp

Landslide susceptibility mapping: A comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey)

✍ E. Yesilnacar; T. Topal 📂 Article 📅 2005 🏛 Elsevier Science 🌐 English ⚖ 806 KB

Landslide susceptibility mapping is one of the most critical issues in Turkey. At present, geotechnical models appear to be useful only in areas of limited extent, because it is difficult to collect geotechnical data with appropriate resolution over larger regions. In addition, many of the physical