@inproceedings{cee5a3f0e77e463581279feda88dfa46,
title = "Characterizing postoperative pain management data by cluster analysis",
abstract = "PCA (Patient Controlled Analgesia) is a delivery system for pain medication that makes effective and flexible pain treatments possible by allowing patients to adjust the dosage of analgesics themselves. Unlike previous research on patient controlled analgesia, this study explores patient demand behavior over time. We applied clustering methods to disclose demand patterns among patients over the first 24h of analgesic medication after surgery. We first identified three demand patterns from patient controlled analgesia request log files. We then considered demographic, biomedical, and surgery-related data to evaluate the influence of demand pattern on analgesic requirements. We recovered several associations that concurred with previous findings, and discovered several new correlations.",
keywords = "Clustering, PCA demand, Patient controlled analgesia, Postoperative pain",
author = "Yuh-Jyh Hu and Jan, {Rong Hong} and Kuo-Chen Wang and Yu-Chee Tseng and Ku, {Tien Hsiung} and Yang, {Shu Fen}",
year = "2012",
month = dec,
day = "1",
language = "English",
isbn = "1601322186",
series = "Proceedings of the 2012 International Conference on Artificial Intelligence, ICAI 2012",
pages = "438--444",
booktitle = "Proceedings of the 2012 International Conference on Artificial Intelligence, ICAI 2012",
note = "2012 International Conference on Artificial Intelligence, ICAI 2012 ; Conference date: 16-07-2012 Through 19-07-2012",
}