pubs2024

@inproceedings{Quintas201629,

title = {A case based approach to assess waiting time prediction at an intensive care unity},

author = {A. Quintas and H. Vicente and P. Novais and A. Abelha and M. F. Santos and J. Machado and J. Neves},

editor = {Arezes P.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84986268659&doi=10.1007%2f978-3-319-41929-9_4&partnerID=40&md5=14537afce594fb1c8883221af2f7b789},

doi = {10.1007/978-3-319-41929-9_4},

issn = {21945357},

year  = {2016},

date = {2016-01-01},

journal = {Advances in Intelligent Systems and Computing},

volume = {491},

pages = {29-39},

publisher = {Springer Verlag},

abstract = {Waiting time at an intensive care unity stands for a key feature in the assessment of healthcare quality. Nevertheless, its estimation is a difficult task, not only due to the different factors with intricate relations among them, but also with respect to the available data, which may be incomplete, self-contradictory or even unknown. However, its prediction not only improves the patients’ satisfaction but also enhance the quality of the healthcare being provided. To fulfill this goal, this work aims at the development of a decision support system that allows one to predict how long a patient should remain at an emergency unit, having into consideration all the remarks that were just stated above. It is built on top of a Logic Programming approach to knowledge representation and reasoning, complemented with a Case Base approach to computing. © Springer International Publishing Switzerland 2016.},

note = {cited By 10; Conference of International Conference on Safety Management and Human Factors, 2016 ; Conference Date: 27 July 2016 Through 31 July 2016; Conference Code:180619},

keywords = {Artificial intelligence; Computation theory; Computer circuits; Decision support systems; Forecasting; Health care; Human engineering; Knowledge representation; Logic programming; Reconfigurable hardware, Case based reasoning, Case-based approach; Healthcare quality; Intensive care; Key feature; Knowledge representation and reasoning; Similarity analysis; Waiting-time; Waiting-time prediction},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Faria2016159,

title = {A case-based approach to nosocomial infection detection},

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

editor = {Rutkowski L. Tadeusiewicz R. Zurada J.M.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84977478473&doi=10.1007%2f978-3-319-39384-1_14&partnerID=40&md5=e0e813cd5ebc01c8fb96823371bff0ff},

doi = {10.1007/978-3-319-39384-1_14},

issn = {03029743},

year  = {2016},

date = {2016-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {9693},

pages = {159-168},

publisher = {Springer Verlag},

abstract = {The nosocomial infections are a growing concern because they affect a large number of people and they increase the admission time in healthcare facilities. Additionally, its diagnosis is very tricky, requiring multiple medical exams. So, this work is focused on the development of a clinical decision support system to prevent these events from happening. The proposed solution is unique once it caters for the explicit treatment of incomplete, unknown, or even contradictory information under a logic programming basis, that to our knowledge is something that happens for the first time. © Springer International Publishing Switzerland 2016.},

note = {cited By 2; Conference of 15th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2016 ; Conference Date: 12 June 2016 Through 16 June 2016; Conference Code:177089},

keywords = {Artificial intelligence; Computation theory; Computer circuits; Decision support systems; Diagnosis; Health care; Knowledge representation; Logic programming; Reconfigurable hardware; Soft computing, Case based reasoning, Case-based approach; Clinical decision support systems; Explicit treatments; Healthcare facility; Knowledge representation and reasoning; Nosocomial infection; Number of peoples; Similarity analysis},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Neves20163,

title = {Screening a case base for stroke disease detection},

author = {J. Neves and N. Gonçalves and R. Oliveira and S. Gomes and J. Neves and J. Macedo and A. Abelha and C. Analide and J. Machado and M. F. Santos and H. Vicente},

editor = {Quintian H. Troncoso A. Martinez-Alvarez F.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964056771&doi=10.1007%2f978-3-319-32034-2_1&partnerID=40&md5=8b11d528fb7c9db682be64a47fb6730e},

doi = {10.1007/978-3-319-32034-2_1},

issn = {03029743},

year  = {2016},

date = {2016-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {9648},

pages = {3-13},

publisher = {Springer Verlag},

abstract = {Stroke stands for one of the most frequent causes of death, without distinguishing age or genders. Despite representing an expressive mortality figure, the disease also causes long-term disabilities with a huge recovery time, which goes in parallel with costs. However, stroke and health diseases may also be prevented considering illness evidence. Therefore, the present work will start with the development of a decision support system to assess stroke risk, centered on a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with a Case Based Reasoning (CBR) approach to computing. Indeed, and in order to target practically the CBR cycle, a normalization and an optimization phases were introduced, and clustering methods were used, then reducing the search space and enhancing the cases retrieval one. On the other hand, and aiming at an improvement of the CBR theoretical basis, the predicates` attributes were normalized to the interval 0…1, and the extensions of the predicates that match the universe of discourse were rewritten, and set not only in terms of an evaluation of its Quality-of-Information (QoI), but also in terms of an assessment of a Degree-of-Confidence (DoC), a measure of oneʼs confidence that they fit into a given interval, taking into account their domains, i.e., each predicate attribute will be given in terms of a pair (QoI, DoC), a simple and elegant way to represent data or knowledge of the type incomplete, self-contradictory, or even unknown. © Springer International Publishing Switzerland 2016.},

note = {cited By 2; Conference of 11th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2016 ; Conference Date: 8 April 2016 Through 20 April 2016; Conference Code:173819},

keywords = {Artificial intelligence; Computation theory; Computer circuits; Decision support systems; Diagnosis; Intelligent systems; Knowledge representation; Logic programming; Quality control; Reconfigurable hardware; Risk assessment, Case based reasoning, Case-based reasoning approaches; Clustering methods; Degree of confidence; Disease detection; Knowledge representation and reasoning; Quality of informations (QoI); Similarity analysis; Universe of discourse},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Neves201565,

title = {A case based approach to concrete deterioration assessment},

author = {J. Neves and G. Gomes and J. Machado and H. Vicente},

editor = {Goto T.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983621556&partnerID=40&md5=a1be21d081d6be22a5b10e366066bed3},

isbn = {9781510812284},

year  = {2015},

date = {2015-01-01},

journal = {28th International Conference on Computer Applications in Industry and Engineering, CAINE 2015},

pages = {65-70},

publisher = {International Society of Computers and Their Applications (ISCA)},

abstract = {The deterioration of concrete infrastructures is of concern since maintenance and repair require large amounts of resources. It is a multifaceted and complex phenomenon, with multiple causes, namely age, use, maintenance, type of environmental exposure and aggression by biological, chemical, mechanical and physical agents. However, it may be prevented if proactive strategies were embraced (e.g., taking into account similar past experiences). Indeed, this work will start with the development of a decision support system to prevent these events from happening, centered on a formal framework based on Logic Programming for knowledge representation, complemented with a Case-Based Reasoning (CBR) approach to problem solving, which caters for the handling of incomplete, unknown, or even contradictory information. The CBR cycle was adapted in order to cater for the developments referred to above, and clustering methods were enforced to distinguish and aggregate collections of historical records in order to reduce the search space and enhance the retrieve phase.},

note = {cited By 0; Conference of 28th International Conference on Computer Applications in Industry and Engineering, CAINE 2015 ; Conference Date: 12 October 2015 Through 14 October 2015; Conference Code:123216},

keywords = {Artificial intelligence; Computer circuits; Concretes; Decision support systems; Deterioration; Knowledge representation; Logic programming; Phase space methods; Problem solving; Reconfigurable hardware; Repair, Case based reasoning, Case-based approach; Case-based reasoning approaches; Clustering methods; Concrete deterioration; Environmental exposure; Knowledge representation and reasoning; Normalization; Similarity analysis},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Duarte2011414,

title = {Towards intelligent drug electronic prescription},

author = {J. Duarte and J. Neves and A. Cabral and M. Gomes and V. Marques and M. F. Santos and A. Abelha and J. MacHado},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84898976033&partnerID=40&md5=d0414e3997b901b8bbe1fab1017bceaa},

year  = {2011},

date = {2011-01-01},

journal = {ESM 2011 - 2011 European Simulation and Modelling Conference: Modelling and Simulation 2011},

pages = {414-418},

publisher = {EUROSIS},

address = {Guimaraes},

abstract = {The errors associated with prescription drugs arc common. The technology will help to reduce the error. The transition from the traditional method of prescription (written manually and on paper) for electronic prescribing of drugs has been done in developed countries. However, there is still some lack of efficicncy. Some of the inefficiencies in the method of electronic prescribing are related to the interface of these systems, based on forms. These systems arc still unwise and less useful as an aid in decision making on prescription. This study attempted to explore the automatic interpretation of text in electronic prescription systems and techniques of Case Based Reasoning for recommending drugs. ©2011 EUROSIS-ETI.},

note = {cited By 2; Conference of 25th European Simulation and Modelling Conference, ESM 2011 ; Conference Date: 24 October 2011 Through 26 October 2011; Conference Code:104378},

keywords = {Case based reasoning, Developed countries; Drug electronic prescription; Electronic health record; Electronic prescription system; Prescription drugs, Modal analysis; Ontology; Terminology},

pubstate = {published},

tppubtype = {inproceedings}

}