Sleep-EVAL Aims

First created | 01/12/1994

Last edited |

Written by Maurice M. Ohayon, MD, DSc, PhD

When the first epidemiological survey was launched in 1992, we were looking for an assessment tool that could be used by interviewers with little knowledge about sleep disorders.

We also wanted a tool that allowed the broad coverage of sleep habits, including sleep/wake schedule and sleep hygiene.
The tool also had to permit the identification of mental disorders most frequently associated with sleep problems; and, most of all, the tool should allow the formulation of sleep diagnoses according to several classifications.
Tools that met all these requirements were nonexistent.
Questionnaires to assess sleep disorders covered only some disorders.
None of them was designed to allow a differential diagnosis making.

HISTORY OF SLEEP-EVAL

Briefly:
- in 1983, creation of Adinfer (©M Ohayon, 1983) a level 0+ expert system devoted to the assessment of psychiatric disorders.
- from 1983 to 1991, Adinfer went through several changes to increase its diagnostic abilities.
- in 1990, creation of Sleep-EVAL (©M Ohayon, 1990), a level-2 expert system endowed with a causal reasoning mode.

The integration of a neural network in an expert system gives "reasoning" aibilities that are the closest to human reasoning at this time.

Indeed, neural networks are able to find solutions to problems that usually require human observations or thought processes.

When used in diagnostic processes, they allow incorporation of subjectivity in answers provided by the subject and manage the resulting uncertainty in the assessment of a disorder.

OBJECTIVES

Sleep-EVAL was developed with clear objectives in mind:

to improve the quality of collected data,
to find new ways to analyze risk factors associated with some abnormalities, and finally,
to provide some kind of validation of the usefulness of existing classifications such as the DSM-IV (APA, 1994), the International Classification of Sleep Disorders (ASDA, 1990, 1997), and the International Classification of Disease (ICD-10, WHO).

The use of fuzzy logic reasoning managed by a neural network was allowing the inclusion of the richness of clinical experience in a tool that can be used by inexperienced interviewers.

MORE INFORMATION

Sleep-Eval Aims

When the first epidemiological survey was launched in 1992, we were looking for an assessment tool that could be used by interviewers with little knowledge about sleep disorders.

Diagnosis Expert System

Sleep-EVAL, an artificial intelligent computer program, is an Expert System for evaluation and diagnosis of Sleep and Mental Disorders in general and clinical populations

Knowledge Base

The inference engine uses its knowledge base to pose questions, to infer hypotheses and to deduce diagnostic conclusions

Inference Engine

Sleep-EVAL is a non-monotonic, level-2 expert system endowed with the ability to make logical connections based on patient information (causal reasoning mode).

Fuzzy Logic

Inference models such as probabilistic and fuzzy systems can be used to integrate uncertainty in both symptomatic assessment and diagnostic attribution. It therefore becomes possible to extend boundaries and attribute a degree of certainty to a diagnosis. A probabilistic model can be easily computed from an existent binary data set. A fuzzy model can also be calculated from an existent data set, but the model is obviously much more precise when the data are expressed in categorical terms.