Active learning for clinical text classification: is it better than random sampling?

Objective: This study explores active learning algorithms as a way to reduce the requirements for large training sets in medical text classification tasks.Design: Three existing active learning algorithms (distance-based (DIST), diversity-based (DIV), and a combination of both (CMB)) were used to cl...

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Bibliographic Details

Published in:	Journal of the American Medical Informatics Association Vol. 19; no. 5; pp. 809 - 817
Main Authors:	Figueroa, Rosa L, Zeng-Treitler, Qing, Ngo, Long H, Goryachev, Sergey, Wiechmann, Eduardo P
Format:	research Journal Article
Published:	Oxford University Press / USA Sep2012
Online Access:	View this record in EBSCOhost