Making it possible to measure knowledge, experience and intuition in diagnosing lung injury severity: a fuzzy logic vision based on the Murray score

BMC Medical Informatics and Decision Making

Research Article

Carlos E D'Negri¹  Eduardo L De Vito² 

[1] Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Combatientes de Malvinas 3150, CP 1427, Buenos Aires, Argentina;Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Combatientes de Malvinas 3150, CP 1427, Buenos Aires, Argentina;Departamento de Neumonología y Laboratorio Pulmonar. Instituto de Investigaciones Médicas Alfredo Lanari, Universidad de Buenos Aires, Buenos Aires, Argentina;

关键词: Membership Function;    Fuzzy Logic;    Acute Lung Injury;    Acute Respiratory Distress Syndrome;    Fuzzy Inference System;   

DOI  :  10.1186/1472-6947-10-70

 received in 2010-04-16, accepted in 2010-11-04,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundMurray score is the result of an equation that gives all its variables the same linear contribution and weight and makes use of consented cut-offs. Everyday physicians' vocabulary is full of terms (adjectives) like: little, small, low, high, etc. that they handle in an intuitive and not always linear way to make therapeutic decisions. The purpose of this paper is to develop a fuzzy logic (FL) vision of Murray's score variables to enable the measurement of physicians' knowledge, experience and intuition in diagnosing lung injury and test if they followed Murray's equation predictions.MethodsFor a prospective survey carried out among a team of professionals (aged 29 to 53) in a University Hospital Intensive Care Unit, twelve physicians filled in two questionnaires. In the first one they had to define the ranks which should be categorized as normal, moderate and severe for three of four Murray variables. In another questionnaire, which represented all probable combinations of those categories, they had to tick the pulmonary condition as: no injury, mild, moderate, and ARDS. This procedure gave rise to a Fuzzy Inference System designed to provide the degree of severity as sensed by the group.ResultsThe survey showed fuzzy frontiers for the categories and fuzzy diagnosis. In all, 45% of the hypothetical patients (n 18,013) were equally diagnosed by the survey and Murray's equation, whereas another 51% was overestimated in one level by the survey. Physicians agreed with 96.5% of ARDS cases according to Murray's test but only 11.6% of its mild cases were equally diagnosed by the survey. Nonlinearity of the survey reasoning (high relevance to gas exchange and chest film) was apparent.ConclusionsThe contiguous categories of the variables confirm the existence of fuzzy frontiers. An overestimation was found in the surveyed group's interpretation of severity. This overestimation was mainly due to the different weight assigned to PO2/FiO2 and chest film variables. The FL approach made it possible to measure knowledge, experience and intuition as they appear in physicians' thinking. FL methodology could overcome a series of restrictions that current tests have due to cut-offs

【 授权许可】

CC BY   
© D'Negri and De Vito; licensee BioMed Central Ltd. 2010