A novel generalized belief structure comprising unprecisiated uncertainty applied to aphasia diagnosis.
Our basic understanding of evidential reasoning, in its vast and intricate complexity, has been guided by different methods including probabilistic and possibilistic models. However, restrictions surrounding evidence must be fully precisiated/validated before discussing their probability or possibil...
| Publicado en: | Journal of Biomedical Informatics Vol. 62; pp. 66 - 78 |
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| Autor principal: | |
| Formato: | research Journal Article |
| Publicado: |
Academic Press Inc.
Aug2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=117443038&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 117443038 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15320464 OMB jtl: Journal of Biomedical Informatics issn: 15320464 maglogo: N pubinfo: dt: Aug2016 vid: 62 pid: 735 pub: Academic Press Inc. place: Burlington, Massachusetts artinfo: ui: 117443038 117443038 NLM27301542 117443038 10.1016/j.jbi.2016.06.004 NLM27301542 117443038 ppf: 66 ppct: 12 formats: tig: atl: A novel generalized belief structure comprising unprecisiated uncertainty applied to aphasia diagnosis. aug: au: Sabahi, Farnaz affil: Department of Electrical Engineering, Faculty of Engineering, University of Urmia, Urmia, Iran sug: subj: Aphasia Diagnosis Probability Models, Statistical Uncertainty Human ab: Our basic understanding of evidential reasoning, in its vast and intricate complexity, has been guided by different methods including probabilistic and possibilistic models. However, restrictions surrounding evidence must be fully precisiated/validated before discussing their probability or possibility which is rarely achieved, especially in uncertain or imprecise environments. In this paper, a new generalization of the Dempster-Shafer Theory (DST) is presented that accounts for this issue. In the proposed generalization, we include information about the validity of a fuzzy body of evidence to represent its bearing on unprecisiated information, and then we distribute this knowledge over the belief structure. We provide an epistemic framework of evidence and study its behavior and its constraints in terms of validity, probability, and possibility to establish a foundation for evidential reasoning and unprecisiated uncertainty that exists in evidence. The suggested belief structure is crafted by min-max optimization method. Then, the proposed structure is used to estimate the probability density function (pdf) and is explored by the application diagnosis of aphasia, in which unprecisiated uncertainty is involved due to the subjectivity of the test items, inconsistency in the interpretation of aphasic syndromes, and the changeable precision of medical tests. Even in requiring more parameters, an accuracy improvement in the results is noticeably observed, especially when compared with the results of alternative approaches applied in the same database. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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