@inproceedings{149895b157514d94b8744f722a8fd4b5,
title = "Relevance ranking of intensive care nursing narratives",
abstract = "Current computer-based patient records provide many capabilities to assist nurses' work in intensive care units, but the possibilities to utilize existing free-text documentation are limited without the appropriate tools. To ease this limitation, we present an adaptation of the Regularized Least-Squares (RLS) algorithm for ranking pieces of nursing notes with respect to their relevance to breathing, blood circulation, and pain. We assessed the ranking results by using Kendall's τb as a measure of association between the output of the RLS algorithm and the desired ranking. The values of τb, were 0.62, 0.69, and 0.44 for breathing, blood circulation, and pain, respectively. These values indicate that a machine learning approach can successfully be used to rank nursing notes, and encourage further research on the use of ranking techniques when developing intelligent tools for the utilization of nursing narratives.",
keywords = "Regularized least-squares, free-text, Nursing notes",
author = "Hanna Suominen and Tapio Pahikkala and Marketta Hussa and Tuija Lehtikunnas and Barbro Back and Helena Karsten and Sanna Salanter{\"a} and Salakoski, {Tapio I.}",
year = "2006",
doi = "10.1007/11892960_87",
language = "English",
isbn = "9783540465355",
volume = "4251",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "720--727",
editor = "Bogdan Gabrys and Howlett, {Robert J.} and Jain, {Lakhmi C.}",
booktitle = "Knowledge-Based Intelligent Information and Engineering Systems - 10th International Conference, KES 2006, Proceedings",
address = "Netherlands",
note = "10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006 ; Conference date: 09-10-2006 Through 11-10-2006",
}