Development of an automated expert system for diagnosing diseases of internal organs

Alua Myrzakerimova, Mugulsum Nurmaganbetova

2020

Closed access Metadata (CSL-JSON)
DOI 10.1145/3410352.3410759
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

This paper presents the research in automated expert systems for diagnosing diseases of internal organs. The paper begins with a review of current medical situation and systems regarding the software process. This is followed by cybernetic approach and the paradigms it uses. The proposed automated expert system is an information program that uses the expert knowledge of a doctor to effectively solve problems in diagnosing diseases. Basically, the system consists of a knowledge base about diseases of internal organs.