2018
Neves, J.; Vicente, H.; Esteves, M.; Ferraz, F.; Abelha, A.; Machado, J.; Machado, J.; Neves, J.
Waiting time screening in healthcare Proceedings Article
Em: K.N., Jung J. J. Kim P. Choi (Ed.): pp. 124-131, Springer Verlag, 2018, ISSN: 18678211, (cited By 1; Conference of 8th International Conference on Big Data Technologies and Applications, BDTA 2017 ; Conference Date: 23 November 2017 Through 24 November 2017; Conference Code:220889).
Resumo | Links | BibTeX | Etiquetas: Asymptomatic patients; Human bodies; Laboratory testing; Medical treatment; Operational data; Type of technology; Various technologies; Waiting-time, Big data; Case based reasoning; Computerized tomography; Decision support systems; Health care; Logic programming; Magnetic resonance; Medical imaging, Diagnosis
@inproceedings{Neves2018124,
title = {Waiting time screening in healthcare},
author = {J. Neves and H. Vicente and M. Esteves and F. Ferraz and A. Abelha and J. Machado and J. Machado and J. Neves},
editor = {Jung J. J. Kim P. Choi K.N.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057187471&doi=10.1007%2f978-3-319-98752-1_14&partnerID=40&md5=ff8c5917c0a23f21c5d0c79c6e4173b3},
doi = {10.1007/978-3-319-98752-1_14},
issn = {18678211},
year = {2018},
date = {2018-01-01},
journal = {Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST},
volume = {248},
pages = {124-131},
publisher = {Springer Verlag},
abstract = {In Medical Imaging (MI), various technologies can be used to monitor the human body for diagnosing, monitoring or treating disease. Each type of technology provides different information about the body area that is being investigated or treated for a possible illness, injury or effectiveness of a medical treatment. Routine screening has identified malfunction detection in many otherwise asymptomatic patient images such as computed tomography or magnetic resonance. Studies have shown that, compared to patients whose disease was symptomatic (i.e., self-recognizing), screen-detected diseases may have more favorable clinicopathological features, leading to better prognosis and better outcome. This paper aims to assess the issue of health care wait screening. It deviates from a decision support system that evaluates the waiting times in diagnostic MI based on operational data from various information systems. Last but not least, one’s assumptions may have an important impact in determining the usefulness of routine laboratory testing at admission. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.},
note = {cited By 1; Conference of 8th International Conference on Big Data Technologies and Applications, BDTA 2017 ; Conference Date: 23 November 2017 Through 24 November 2017; Conference Code:220889},
keywords = {Asymptomatic patients; Human bodies; Laboratory testing; Medical treatment; Operational data; Type of technology; Various technologies; Waiting-time, Big data; Case based reasoning; Computerized tomography; Decision support systems; Health care; Logic programming; Magnetic resonance; Medical imaging, Diagnosis},
pubstate = {published},
tppubtype = {inproceedings}
}
In Medical Imaging (MI), various technologies can be used to monitor the human body for diagnosing, monitoring or treating disease. Each type of technology provides different information about the body area that is being investigated or treated for a possible illness, injury or effectiveness of a medical treatment. Routine screening has identified malfunction detection in many otherwise asymptomatic patient images such as computed tomography or magnetic resonance. Studies have shown that, compared to patients whose disease was symptomatic (i.e., self-recognizing), screen-detected diseases may have more favorable clinicopathological features, leading to better prognosis and better outcome. This paper aims to assess the issue of health care wait screening. It deviates from a decision support system that evaluates the waiting times in diagnostic MI based on operational data from various information systems. Last but not least, one’s assumptions may have an important impact in determining the usefulness of routine laboratory testing at admission. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.