@inproceedings{9bb0458e563b47d3af5301dcd7e748b4,
title = "Towards a classifier for predicting cardiovascular events using privileged information",
abstract = "Learning Using Privileged Information (LUPI) is a learning paradigm that aims to improve supervised learning in the presence of additional (privileged) information available during training, but not during the testing phase. For example, the Multi-Ethnic Study of Atherosclerosis (MESA) used in epidemiological studies related to heart disease, contains data from 186 attributes, only eight of which are used in current risk prediction algorithms.",
keywords = "LUPI, MESA, Privileged information",
author = "G. Giannoulis and Yotov, {S. V.} and M. Naghavi and M. Budoff and Kakadiaris, {I. A.}",
note = "Publisher Copyright: Copyright 2014 ACM.; 7th ACM International Conference on Pervasive Technologies Related to Assistive Environments, PETRA 2014 ; Conference date: 27-05-2014 Through 30-05-2014",
year = "2014",
month = may,
day = "27",
doi = "10.1145/2674396.2674434",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
booktitle = "Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2014",
}