Measurement and valuation of a fuzzy mathematical model for medical diagnosis

Esogbue, Augustine O.; Elder, Robert Craig

doi:10.1016/s0165-0114(83)80117-1

Cited by 51 publications

(12 citation statements)

References 11 publications

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“…Few studies have investigated different ways of thinking about assessment: that raters have good, even if somewhat imprecise, language-mediated reasons (heuristics) for making their assessments. Such an approach acknowledges and builds on the rationality of human endeavors (Garfinkel, 1967); it models these endeavors even in the face of uncertainty, ambiguity, and variations with which assessment objects can be perceived, described, interpreted, or appreciated (Esogbue & Elder, 1983). In this study, we present such an approach that models how the imprecise descriptions provided while assessors talk to and for each other about the performances of pilots lead to specific scores that they attribute to these performances.…”

Section: Discussionmentioning

confidence: 99%

Assessment of Nontechnical Skills

Roth

Mavin

2013

Aviation Psychology and Applied Human Factors

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The assessment of pilots’ performances and more specifically their nontechnical skills turns out to be difficult because researchers and practitioners find that inter-rater reliability tends to be moderate to low. In this study, we proposed, consistent with field observations, that assessment is a categorization rather than a measurement issue. Categorization, even though, and especially when, based on imprecise information and assessments, can be modeled mathematically using fuzzy logic. We present the structure of the approach and provide an example from a large database of pilots providing reasons for their assessments of other pilots’ (simulator) flying performances. Considering the implications, we discuss possibilities for using the variations in performance ratings positively, as a source for learning and resilience building.

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Section: Discussionmentioning

confidence: 99%

Assessment of Nontechnical Skills

Roth

Mavin

2013

Aviation Psychology and Applied Human Factors

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“…In applications numeric representations of linguistic variables are usually normalised since there is no common measurement scale between variables Koczy 1993]; there is also often a measure of relative importance attached to different linguistic variables. Relative importance can be handled Esbogue 1980, Esbogue 1983, Zimmermann 1990, Yager 1978] by applying a weighting to each variable, using extended scalar multiplication. The relative weight of variables can be obtained by techniques such as Saaty's Saaty 1980] Analytic Hierarchy Process.…”

Section: Weighted Linguistic Variablesmentioning

confidence: 99%

Reasoning with Non-Numeric Linguistic Variables

Williams¹,

Steele²,

Robinson³

2002

CIT

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Where decisions are based on imprecise numeric data and linguistic variables, the development of automated decision aids presents particular difficulties. In such applications, linguistic variables often take their values from a pre-ordered set of vaguely defined linguistic terms. The mathematical structures that arise from the assumption that sets of linguistic terms are pair-wise tolerant are considered. A homomorphism between tolerance spaces, filter bases and fuzzy numbers is shown. A proposal for modeling linguistic terms with an ordered set of fuzzy numbers is introduced. A procedure for structured knowledge acquisition based on the topology of the term sets and the cognitive theory of prototypes is shown to give rise to sparse rule bases. Similarity as a function of "distance" between fuzzy numbers treated as tolerance mappings is used as an inference mechanism in sparse rule bases to give linguistically valued outputs. Measuring the "distance" between fuzzy sets to correspond to intuitive notions of nearness is not straightforward, since the usual metric axioms are not adequate. An alternative way of measuring "distance" between fuzzy numbers is introduced, which reduces to the usual one when applied to crisp numbers.

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“…MYCIN did not use fuzzy logic directly; one of primary components was the use of certainty factors. The medical expert systems using fuzzy logic directly are given in the references [3], [4] and [5]. Fuzzy degree of uncertainty or possibility degree of certain diagnosis is employed, as explained in [3], [4] and [5].…”

Section: Introductionmentioning

confidence: 99%

“…The medical expert systems using fuzzy logic directly are given in the references [3], [4] and [5]. Fuzzy degree of uncertainty or possibility degree of certain diagnosis is employed, as explained in [3], [4] and [5]. Artificial Intelligence (AI) is the study of mental facilities through the use of computational models.…”

Section: Introductionmentioning

confidence: 99%

FFANN Based Cost Effective Major Infant Disease Management

Agarkar¹,

Ghatol²

2010

IJCA

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In India, 30% to 40 % babies are low birth weight babies (LBW) as opposed to about 5% to 7% of newborn in the west. In India, 7 to 10 million LBW infants are born annually. About 10 % to 12% of Indian babies are born preterm (less than 37 completed weeks) as compared with 5% to 7% incidence in the west. These infants are physically immature and therefore their neonatal mortality is high. It is possible to increase the survival of the infants and quality of human life through prompt and adequate disease management of the newborn. The proposed model of cost effective major infant disease management system based on artificial intelligence algorithm is helpful for diagnostic-cum-preventive approach to reduce the immaturity, fragility, vulnerability and dependence of the neonates in the developing countries to reduce neonatal and child mortality. Secondly, a significant proportion of the pediatricians" time, especially in major hospitals, large cities and overpopulated areas is spent on examination and evaluation of apparently healthy babies and detection of minor developmental defects. In addition to these facts, many third world countries including countries like Pakistan and Bangladesh face the major problem of child health diagnosis and malnutrition. Medical facilities and expertise is either absent or out of reach of these tribal and poor communities, many public health centers (PHCs) lack in advice by experts on immediate basis in case of emergencies. Major hurdles include the lack of medical experts and trained manpower, scarcity of funds and improper budgetary allocation for rural health at state and central government level.

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Measurement and valuation of a fuzzy mathematical model for medical diagnosis

Cited by 51 publications

References 11 publications

Assessment of Nontechnical Skills

Assessment of Nontechnical Skills

Reasoning with Non-Numeric Linguistic Variables

FFANN Based Cost Effective Major Infant Disease Management

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