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The applications accessible from this site are for demonstration purposes only. They have not been validated for clinical use and must not be used for real patient encounters.


Demonstrations of clinical applications
Brazil   Niaclin

Sistema Especialista em Medicina / Web-based diagnostic expert system

developed by clinical domains keywords
Roberto Silva, Adventist University of São Paulo Multiple Expert systems, rule-based, knowledge representation, diagnosis, advisor
status access demonstrator
Demonstrator developed 2005  bullet  Niaclin
description

Niaclin is a rule-based medical expert system designed to provide advice for medical symptoms. The Niaclin knowledge base currently contains 116 diseases and 128 symptoms. The top ten hyphoteses are listed for each query (allowing for differential diagnosis), and links to these principal hypotheses are provided.

Niaclin is a web-based version of Niacin, a medical expert system and expert system shell developed in 1995. The Niacin shell worked with several knowledge bases including exanthematic diseases, causes of purpura, abdominal pain, vaginitis.

Niaclin is based in part on techniques used in Mycin (belief and disbelief measures), Internist (descriptors associated with diseases according to the frequency of the symptoms in diseases; intrinsic value of symptoms) and in Addlasnig's CADIAG (numeric values related to semantic variables).

Niaclin uses six main rules to make a diagnosis and provide advice. The system takes account of:
  1. Symptoms present in a patient and described as related to a disease stored in the knowledge base
  2. Symptoms present in a patient but not specified as related to disease specified in the knowledge base
  3. Symptoms not present in a patient but described as to a disease specified in the knowledge base
  4. Symptoms not present in a patient and not linked to a disease stored in the knowledge base
  5. Symptoms present in a patient but not included in a disease description in the knowledge base
  6. Symptoms not present in patient and not included in a disease description in the knowledge base.

Rules 1, 4 and 6 refer to positive findings and are used to increase the belief measure (MB). Rules 2, 3 and 5 refer to negative findings and are used to decrease the belief measure (MD). Confidence values are obtained by the difference between MB and MD. The basic formula used for calculating the final confidence value in the system is:
    MB = MB + [ ( 1- MB) * confirmability * intrinsic value of symptom)]

Confidence in belief measures increases according to the frequency of symptoms linked to diseases, the relative importance of symptoms, the frequency of symptoms in the NIACLIN knowledge base and may vary according to the knowledge base rules. These and similar techniques are used by several medical expert systems. With Niaclin, better results are obtained when both positive and negative findings observed in a patient are input in the system.

references

in Portuguese   Silva R, Parize MMG. NIACIN: Um Programa para o Desenvolvimento de Sistemas Especialistas em Medicina. Revista Informédica, 2 (11): 3-16, 1995. (Brasil)

[informaticamedica.org.br]   []

in Portuguese   " Desde o desenvolvimento da Inteligência Artificial, têm surgido diversos sistemas de apoio ao diagnóstico médico (SADMs), voltados a várias especialidades, tais como medicina interna, doenças bacterianas, doenças renais, etc. Estes programas são denominados de sistemas especialistas, ou sistemas expert, e podem funcionar de diversas maneiras, sendo a mais comum uma consulta com base em questionamento do usuário. O mesmo fornece sintomas e sinais do paciente, e o programa elabora raciocínios lógicos e plausíveis a partir dessa informação, fornecendo, então, os prováveis diagnósticos. Esses raciocínios automatizados utilizam uma base de conhecimentos sobre a especialidade médica em questão, armazenada previamente no computador. Na evolução da Inteligência Artificial em Medicina, inicialmente cada SADM correspondia a um programa especialmente desenvolvido para este fim. Posteriormente, entretanto, surgiram programas gerais, denominados "shell", ou "vazios", que permitem se possa trabalhar com diferentes bases de conhecimento, usando um mesmo programa. O surgimento de versões comercialmente disponíveis de programas `shell" em Inteligência Artificial aumentou significativamente o número de sistemas especialistas desenvolvidos em Medicina, devido à facilidade que os mesmos oferecem. "

contact links
Dr. Roberto Silva
Health Family Program
UNASP - Adventist University of São Paulo
Brazil

E: niaclinatniaclin.com

 bullet  Niaclin  bullet  UNASP
acknowledgements
Dr. Roberto Silva, Adventist University of São Paulo.
Entry on OpenClinical: 06 May 2005
Last main update: 11 May 2005

 

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