pubs2024

@inproceedings{Vaz2023850,

title = {Enhancing Clinical Management of Bariatric Surgery Using Business Intelligence},

author = {L. Vaz and H. Peixoto and J. Duarte and C. Alvarez and J. Machado},

editor = {Shakshuki E.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164522803&doi=10.1016%2fj.procs.2023.03.114&partnerID=40&md5=33c5a7e1ee9afa79be7d332a07083b79},

doi = {10.1016/j.procs.2023.03.114},

issn = {18770509},

year  = {2023},

date = {2023-01-01},

journal = {Procedia Computer Science},

volume = {220},

pages = {850-855},

publisher = {Elsevier B.V.},

abstract = {There is a problem with collecting information in healthcare services as it is scattered among various sources. This leads to potential impact on patient care focus. To address this issue, a Business Intelligence platform was developed and implemented at the Centre for Surgical Treatment of Obesity at Centro Hospitalar do Tâmega e Sousa. The platform developed enables knowledge extraction and aids healthcare professionals to easily access helpful information and perform better decisions, specifically in regards to the growing global concern of obesity and the increasing prevalence of bariatric surgery. © 2023 Elsevier B.V.. All rights reserved.},

note = {cited By 0; Conference of 14th International Conference on Ambient Systems, Networks and Technologies Networks, ANT 2023 and The 6th International Conference on Emerging Data and Industry 4.0, EDI40 2023 ; Conference Date: 15 March 2023 Through 17 March 2023; Conference Code:189712},

keywords = {Bariatric surgery; Business Intelligence platform; Business-intelligence; Clinical management; Healthcare services; Knowledge extraction; Obesity; Patient care; Potential impacts; Surgical treatment, Extraction, Information analysis; Nutrition; Surgery},

pubstate = {published},

tppubtype = {inproceedings}

}