Publication
Bayesian and Artificial Neural Networks Algorithms at Myocardial Perfusion Imaging
| dc.contributor.author | Vieira, Domingos | |
| dc.contributor.author | Nogueira, Fábio | |
| dc.contributor.author | Metello, Luís F. | |
| dc.date.accessioned | 2015-07-09T15:56:38Z | |
| dc.date.available | 2015-07-09T15:56:38Z | |
| dc.date.issued | 2011-10 | |
| dc.description.abstract | One major focus of data mining process - especially Machine Learning researches - relates to automatically learn to recognize complex patterns and help to take the adequate decisions strictly based on the acquired data. In a preliminary study, advantages on Computerized Analysis of data over Human Analysis in MPI - Myocardial Perfusion Imaging context were identified (shorter time, homogeneity and consistency, automatic recording of analysis results, relatively inexpensive, etc), especially when considering the use of Naïve Bayes algorithm. | en |
| dc.identifier.uri | http://hdl.handle.net/10400.22/6424 | |
| dc.language.iso | por | por |
| dc.peerreviewed | yes | por |
| dc.title | Bayesian and Artificial Neural Networks Algorithms at Myocardial Perfusion Imaging | por |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Birmingham | por |
| oaire.citation.title | Annual Congress of the European Association of Nuclear Medicine | por |
| person.identifier.ciencia-id | 991E-B484-9248 | |
| person.identifier.orcid | 0000-0002-4094-700X | |
| rcaap.rights | openAccess | por |
| rcaap.type | conferenceObject | |
| relation.isAuthorOfPublication | 9503d68a-7431-4e6a-bc8a-315592daa71f | |
| relation.isAuthorOfPublication.latestForDiscovery | 9503d68a-7431-4e6a-bc8a-315592daa71f |