BMC Med Inform Decis Mak - A genetic fuzzy system for unstable angina risk assessment.

Tópicos

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Resumo

CKGROUND: Unstable Angina (UA) is widely accepted as a critical phase of coronary heart disease with patients exhibiting widely varying risks. Early risk assessment of UA is at the center of the management program, which allows physicians to categorize patients according to the clinical characteristics and stratification of risk and different prognosis. Although many prognostic models have been widely used for UA risk assessment in clinical practice, a number of studies have highlighted possible shortcomings. One serious drawback is that existing models lack the ability to deal with the intrinsic uncertainty about the variables utilized.METHODS: In order to help physicians refine knowledge for the stratification of UA risk with respect to vagueness in information, this paper develops an intelligent system combining genetic algorithm and fuzzy association rule mining. In detail, it models the input information's vagueness through fuzzy sets, and then applies a genetic fuzzy system on the acquired fuzzy sets to extract the fuzzy rule set for the problem of UA risk assessment.RESULTS: The proposed system is evaluated using a real data-set collected from the cardiology department of a Chinese hospital, which consists of 54 patient cases. 9 numerical patient features and 17 categorical patient features that appear in the data-set are selected in the experiments. The proposed system made the same decisions as the physician in 46 (out of a total of 54) tested cases (85.2%).CONCLUSIONS: By comparing the results that are obtained through the proposed system with those resulting from the physician's decision, it has been found that the developed model is highly reflective of reality. The proposed system could be used for educational purposes, and with further improvements, could assist and guide young physicians in their daily work.

Resumo Limpo

ckground unstabl angina ua wide accept critic phase coronari heart diseas patient exhibit wide vari risk earli risk assess ua center manag program allow physician categor patient accord clinic characterist stratif risk differ prognosi although mani prognost model wide use ua risk assess clinic practic number studi highlight possibl shortcom one serious drawback exist model lack abil deal intrins uncertainti variabl utilizedmethod order help physician refin knowledg stratif ua risk respect vagu inform paper develop intellig system combin genet algorithm fuzzi associ rule mine detail model input inform vagu fuzzi set appli genet fuzzi system acquir fuzzi set extract fuzzi rule set problem ua risk assessmentresult propos system evalu use real dataset collect cardiolog depart chines hospit consist patient case numer patient featur categor patient featur appear dataset select experi propos system made decis physician total test case conclus compar result obtain propos system result physician decis found develop model high reflect realiti propos system use educ purpos improv assist guid young physician daili work

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