pubs2024

@inproceedings{Esteves2017274,

title = {A case based methodology for problem solving aiming at knee osteoarthritis detection},

author = {M. Esteves and H. Vicente and J. Machado and V. Alves and J. Neves},

editor = {Deris M. M. Nawi N.M. Ghazali R.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009818557&doi=10.1007%2f978-3-319-51281-5_28&partnerID=40&md5=95f00ae4942f7bfa66438104f16f7c1a},

doi = {10.1007/978-3-319-51281-5_28},

issn = {21945357},

year  = {2017},

date = {2017-01-01},

journal = {Advances in Intelligent Systems and Computing},

volume = {549 AISC},

pages = {274-284},

publisher = {Springer Verlag},

abstract = {Knee osteoarthritis is the most common type of arthritis and a major cause of impaired mobility and disability for the ageing populations. Therefore, due to the increasing prevalence of the malady, it is expected that clinical and scientific practices had to be set in order to detect the problem in its early stages. Thus, this work will be focused on the improvement of methodologies for problem solving aiming at the development of Artificial Intelligence based decision support system to detect knee osteoarthritis. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory information. © Springer International Publishing AG 2017.},

note = {cited By 1; Conference of The 2nd International Conference on Soft Computing and Data Mining, SCDM-2016 ; Conference Date: 18 August 2016 Through 20 August 2016; Conference Code:188139},

keywords = {Ageing population; Case based; Case-based approach; Knee osteoarthritis; Knowledge representation and reasoning; X-ray image, Artificial intelligence; Case based reasoning; Computation theory; Computer circuits; Data mining; Decision support systems; Feature extraction; Knowledge representation; Logic programming; Soft computing, Problem solving},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Coimbra2016115,

title = {Prediction of length of hospital stay in preterm infants a case-based reasoning view},

author = {A. Coimbra and H. Vicente and A. Abelha and M. Filipe Santos and J. Machado and J. Neves and J. Neves},

editor = {Czarnowski I. Howlett R.J. Jain L.C.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84977097691&doi=10.1007%2f978-3-319-39630-9_10&partnerID=40&md5=6289feafb914ab92696ef065ab6419ed},

doi = {10.1007/978-3-319-39630-9_10},

issn = {21903018},

year  = {2016},

date = {2016-01-01},

journal = {Smart Innovation, Systems and Technologies},

volume = {56},

pages = {115-128},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {The length of stay of preterm infants in a neonatology service has become an issue of a growing concern, namely considering, on the one hand, the mothers and infants health conditions and, on the other hand, the scarce healthcare facilities own resources. Thus, a pro-active strategy for problem solving has to be put in place, either to improve the quality-of-service provided or to reduce the inherent financial costs. Therefore, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a case-based problem solving methodology to computing, that caters for the handling of incomplete, unknown, or even contradictory information. The proposed model has been quite accurate in predicting the length of stay (overall accuracy of 84.9 %) and by reducing the computational time with values around 21.3 %. © Springer International Publishing Switzerland 2016.},

note = {cited By 1; Conference of 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016 ; Conference Date: 15 June 2016 Through 17 June 2016; Conference Code:177269},

keywords = {Artificial intelligence; Case based reasoning; Computation theory; Computer circuits; Decision support systems; Knowledge representation; Logic programming; Program diagnostics; Quality of service; Reconfigurable hardware, Diagnosis decision; Healthcare facility; Knowledge representation and reasoning; Length of hospital stays; Length of stay; Neonatology; Overall accuracies; Preterm infants, Problem solving},

pubstate = {published},

tppubtype = {inproceedings}

}