@inproceedings{724f84952c66413b9ddf5fea0e650d78,
title = "Towards intelligent decision making for risk screening",
abstract = "Predicting the best next test for medical diagnosis is crucial as it can speed up diagnosis and reduce medical expenses. This determination should be made by fully utilizing the available information in a personalized manner for each patient. In this paper, we propose a method that uses synthesis to infer the best learning cohort for the patient under consideration. The constrained sample space is then used to select the best next test by maximizing the expected information gain.",
keywords = "Information gain, Synthesis",
author = "Panagiotis Moutafis and Kakadiaris, \{Ioannis 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 = "10.1145/2674396.2674431",
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",
address = "United States",
}