@inproceedings{37de5569abc64dbfb90cf51af95b1fca,
title = "Prediction of postoperative recovery based on a computational rules extractor",
abstract = "One important factor for the patients in a postoperative recovery is hypothermia. The doctor must decide whether the patients should be sent to another place with better medical therapy. We therefore adopt the proposed PSO (particle swarm optimization) based Fuzzy classifier to retrieve the crisp rules from the postoperative given medical data from UCI machine learning database, where the rules can be used to assist in doctor diagnosis. The average correct ratio of our prediction for the postoperative recovery is about 84%.",
keywords = "fuzzy system, neural network, postoperative recovery",
author = "Hsieh, {Yi Zeng} and Wang, {Chen Hsu} and Su, {Mu Chun} and Lu, {Ching Hu} and Yu, {Jen Chih} and Chiang, {Yi Min}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2nd IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015 ; Conference date: 06-06-2015 Through 08-06-2015",
year = "2015",
month = aug,
day = "20",
doi = "10.1109/ICCE-TW.2015.7216928",
language = "???core.languages.en_GB???",
series = "2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "332--333",
booktitle = "2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015",
}