2017
Neto, C.; Peixoto, H.; Abelha, V.; Abelha, A.; Machado, J.
Knowledge Discovery from Surgical Waiting lists Proceedings Article
Em: M.M., Peppard J. Varajao J. E. Cruz-Cunha (Ed.): pp. 1104-1111, Elsevier B.V., 2017, ISSN: 18770509, (cited By 9; Conference of International Conference on ENTERprise Information Systems, CENTERIS 2017, International Conference on Project MANagement, ProjMAN 2017 and International Conference on Health and Social Care Information Systems and Technologies, HCist 2017 ; Conference Date: 8 November 2017 Through 10 November 2017; Conference Code:133143).
Resumo | Links | BibTeX | Etiquetas: Artificial intelligence; Classification (of information); Decision support systems; Extraction; Health care; Information management; Information systems; Knowledge representation; Project management; Surgery, Data collection; Data mining applications; Healthcare industry; Knowledge discovery in data basis; Knowledge discovery in database; Pattern discovery; Surgical waiting lists; Waiting lists, Data mining
@inproceedings{Neto20171104,
title = {Knowledge Discovery from Surgical Waiting lists},
author = {C. Neto and H. Peixoto and V. Abelha and A. Abelha and J. Machado},
editor = {Peppard J. Varajao J.E. Cruz-Cunha M.M.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040217774&doi=10.1016%2fj.procs.2017.11.141&partnerID=40&md5=f1a8b6d40ae079b7d7e26aef6b8e7e7c},
doi = {10.1016/j.procs.2017.11.141},
issn = {18770509},
year = {2017},
date = {2017-01-01},
journal = {Procedia Computer Science},
volume = {121},
pages = {1104-1111},
publisher = {Elsevier B.V.},
abstract = {Methods for knowledge discovery in data bases (KDD) have been studied for more than a decade. New methods are required owing to the size and complexity of data collections in administration, business and science. They include procedures for data query and extraction, for data cleaning, data analysis, and methods of knowledge representation. The part of KDD dealing with the analysis of the data has been termed data mining. Data mining is the process of pattern discovery and extraction where huge amount of data is involved. Data mining has been used intensively and extensively by many organizations. In healthcare, data mining is becoming increasingly popular, if not increasingly essential. Data mining applications can greatly benefit all parties involved in the healthcare industry. In this work is presented an approach for the use of data mining in the context of waiting lists for surgery, namely for predicting the type of surgery (programmed or additional) for a record in the list. © 2017 The Authors. Published by Elsevier B.V.},
note = {cited By 9; Conference of International Conference on ENTERprise Information Systems, CENTERIS 2017, International Conference on Project MANagement, ProjMAN 2017 and International Conference on Health and Social Care Information Systems and Technologies, HCist 2017 ; Conference Date: 8 November 2017 Through 10 November 2017; Conference Code:133143},
keywords = {Artificial intelligence; Classification (of information); Decision support systems; Extraction; Health care; Information management; Information systems; Knowledge representation; Project management; Surgery, Data collection; Data mining applications; Healthcare industry; Knowledge discovery in data basis; Knowledge discovery in database; Pattern discovery; Surgical waiting lists; Waiting lists, Data mining},
pubstate = {published},
tppubtype = {inproceedings}
}