We conducted a study to develop the prediction models using ANN analyses based on a dataset obtained from a large-scale population-based cross-sectional study.
This study was based on a dataset generated by record linkage between three population-based registers, the Regional Quality Register of Breast Cancer of the Uppsala/Örebro Region in Central Sweden, the National Population Register, and the LISA-database (an integrated database for labour market research).
Geometric and densitometric specifications were based on a dataset of healthy volunteers and osteopenic patients.
They were built based on a dataset comprising about 200 known compounds.
This study is based on a dataset collected in Sydney, Australia, composed of fingerprints belonging to more than 8000 devices.
Our study is based on a dataset obtained from 500 customers of the company ohmconnect, the only third-party residential DR provider in California.
The study is based on a dataset of approximately 450,000 EPO granted patents and 24,000 patent opposition cases in the years 2000 2008.
Our experimental results based on a dataset of 375 malware samples containing 182927 strings and 12721 Java classes provide an accuracy of 99%.
This is based on a dataset of issuance spreads, ratings and other relevant bond variables including 7232 eurobonds issued by an internationally-diversified sample during 1991 2003.
Our findings are based on a dataset of 4968 experimental choices made by 414 German residential consumers, collected in a stated preference survey.
In this study, we developed a global-scale regression model for MAF based on a dataset unprecedented in size, using observations of discharge and catchment characteristics from 1885 catchments worldwide, measuring between 2 and 106 km2.
