Medical diagnosis as a linguistic game

Abstract Background We present a formalized medical knowledge system using a linguistic approach combined with a semantic net. Method Diseases are defined and coded by natural linguistic terms and linked via a complex network of attributes, categories, classes, lists and other semantic conditions. R...

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Bibliographic Details
Main Authors: Peter Fritz, Andreas Kleinhans, Florian Kuisle, Patricius Albu, Christine Fritz-Kuisle, Mark Dominik Alscher
Format: Article
Language:English
Published: BMC 2017-07-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12911-017-0488-3
Description
Summary:Abstract Background We present a formalized medical knowledge system using a linguistic approach combined with a semantic net. Method Diseases are defined and coded by natural linguistic terms and linked via a complex network of attributes, categories, classes, lists and other semantic conditions. Results We have isolated more than 4600 disease entities (termed pathosoms using a made-up word) with more than 100.000 attributes sets (termed pathophemes using a made-up word) and a semantic net with more than 140.000 links. All major-medical thesauri like ICD, ICD-O and OPS are included. Conclusions Memem7 is a linguistic approach to medical knowledge approach. With the system, we performed a proof of concept and we conclude from our data that our or similar approaches provides reliable and feasible tools for physicians given a formalized history taking is available. Our approach can be considered as both a linguistic game and a third opinion to a set of patient’s data.
ISSN:1472-6947