@inproceedings{fd98a1f434f346b7a21617f258a18303,
title = "An efficient feature selection algorithm for computer-aided polyp detection",
abstract = "We present an efficient feature selection algorithm for computer aided detection (CAD) computed tomographic (CT) colonography. The algorithm 1) determines an appropriate piecewise linear network (PLN) model based on a learning theorem for the given data set, 2) applies the orthonormal least square (OLS) procedure to the PLN model utilizing a Modified Schmidt procedure, and 3) uses a floating search algorithm to select features that minimize the output variance. The undesirable {"}nesting effect{"} is prevented by the floating search approach, and the piecewise linear OLS procedure makes this algorithm very computationally efficient because the Modified Schmidt procedure only requires one data pass during the whole searching process. The selected features are compared to those selected by other methods, through cross-validation with a committee of support vector machines (SVMs).",
author = "Jiang Li and Jianghua Yao and Summers, {Ronald M.} and Amy Hara",
year = "2005",
language = "English (US)",
isbn = "1577352343",
series = "Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2005 - Recent Advances in Artifical Intelligence",
pages = "381--386",
editor = "I. Russell and Z. Markov",
booktitle = "Recent Advances in Artifical Intelligence - Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2005",
note = "Recent Advances in Artifical Intelligence - Eighteenth International Florida Artificial Intelligence Research Society Conference, FLAIRS 2005 ; Conference date: 15-05-2005 Through 17-05-2005",
}