✦ LIBER ✦

A retrospective analysis of the utility of an artificial neural network to predict ED volume

✍ Scribed by Menke, Nathan Benjamin; Caputo, Nicholas; Fraser, Robert; Haber, Jordana; Shields, Christopher; Menke, Marie Nam

Book ID: 122301319
Publisher: Elsevier Science
Year: 2014
Tongue: English
Weight: 461 KB
Volume: 32
Category: Article
ISSN: 1532-8171
DOI: 10.1016/j.ajem.2014.03.011

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

An artificial neural network to predict

An artificial neural network to predict the outcome of repeat prostate biopsies

✍ Mesut Remzi; Theodore Anagnostou; Vincent Ravery; Alexandre Zlotta; Carsten Step 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 138 KB

An evaluation model of artificial neural

An evaluation model of artificial neural network to predict stable width in gravel bed rivers

✍ A. Tahershamsi; M. R. Majdzade Tabatabai; R. Shirkhani 📂 Article 📅 2012 🏛 Springer-Verlag 🌐 English ⚖ 696 KB

Application of an artificial neural netw

Application of an artificial neural network to predict specific class I MHC binding peptide sequences

✍ Milik, Mariusz; Sauer, Dean; Brunmark, Anders P.; Yuan, Lunli; Vitiello, Antonel 📂 Article 📅 1998 🏛 Nature Publishing Group 🌐 English ⚖ 486 KB

An artificial neural network approach to

An artificial neural network approach to prediction of the colorimetric values of the stripped cotton fabrics

✍ Onur Balci; S. Noyan Oğulata; Cenk Şahin; R. Tuğrul Oğulata 📂 Article 📅 2008 🏛 The Korean Fiber Society 🌐 English ⚖ 465 KB

The application of a coupled artificial

The application of a coupled artificial neural network and fault tree analysis model to predict coal and gas outbursts

✍ Zhang Ruilin; Ian S. Lowndes 📂 Article 📅 2010 🏛 Elsevier Science 🌐 English ⚖ 743 KB

This paper proposes the use of a coupled fault tree analysis (FTA) and artificial neural network (ANN) model to improve the prediction of the potential risk of coal and gas outburst events during the underground mining of thick and deep Chinese coal seams. The model developed has been used to invest

Prediction of the strength of mineral ad

Prediction of the strength of mineral admixture concrete using multivariable regression analysis and an artificial neural network

✍ U. Atici 📂 Article 📅 2011 🏛 Elsevier Science 🌐 English ⚖ 448 KB