Towards application of FML in suspicion of non-common diseases

Abstract

In this paper we present the preliminary results of application of Fuzzy Markup Language (FML) to suspect a non-common disease. Under non-common diseases we understand rare diseases. From the broad point of view this problem belongs to the computer-assisted decision support in medical diagnostics and can be supported by fuzzy logic controllers. We can use conventional methods to diagnose a rare disease if it can be exhibited by outstanding symptoms. For example, there are several search machines and data banks that allow to find a rare disease clearly exhibited by a patient's symptoms/signs. But it is very difficult to diagnose a rare disease if it masks as a common disease. Diagnostic of rare diseases is connected with lack, uncertainty and imprecision of knowledge, medical mistake and even medical failure. Additionally, very often a common disease is also established with some degree of belief, thus, the expressions such as "it is possible that a patient has a particular disease" rather often present in the daily medical practice. It is clear that if we would know the common diseases, then deviations from them can be considered as a sign of non-common diseases. In this paper we investigate such deviations with the help of FML. We show how FML mechanism can be adjusted to suspect a rare disease, and discuss the appropriateness of the available operators. © 2011 IEEE

Diagnosis support systems for rare diseases: a scoping review

“…Four articles were excluded at the end of this process with an agreement of the three reviewers. More precisely, we excluded studies aiming to assess severity [8], to assess longitudinal data of cases and controls [9], describing big data management software with one example on genetic disease [10] and aiming to identify "noncommon" diseases without performing a diagnosis [11]. Sixty-eight articles were consequently retained at the end of the whole process ( Fig.…”