EPA-0542 - New Tools for New Psychiatry: the Change Offered by Fuzzy Logic Algorithms

Abstract

Introduction:

The management of non-linear and grey clinical data, so frequent in psychiatry, needs the development of new statistical tools, able to give value to subjectivity and complexity of the observed changes.

Objectives:

A comparison between soft computing models, psychodynamic theory and clinical observations in the experience of psychiatric rehabilitation.

Aims:

To test the use of some dynamic fuzzy algorithms (like clustering, ellipsoidal rules, least square method) in order to improve data analysis in the field of clinical research in psychiatry.

Observations:

The role of slow, evolutionary, multifactorial, minute movements and their potential significance become readable, especially referred to the subjective observations of the clinical operators.

Conclusions:

In this work, that it's necessary to consider only a first step, seems that Dynamic Fuzzy Functions may have a future role in the development of new assessments of clinical data in psychiatry.