Cargando…
Knowledge Discovery from Medical Data and Development of an Expert System in Immunology
Artificial intelligence is one of the fastest-developing areas of science that covers a remarkably wide range of problems to be solved. It has found practical application in many areas of human activity, also in medicine. One of the directions of cooperation between computer science and medicine is...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8228842/ https://www.ncbi.nlm.nih.gov/pubmed/34073080 http://dx.doi.org/10.3390/e23060695 |
_version_ | 1783712837049253888 |
---|---|
author | Pac, Małgorzata Mikutskaya, Irina Mulawka, Jan |
author_facet | Pac, Małgorzata Mikutskaya, Irina Mulawka, Jan |
author_sort | Pac, Małgorzata |
collection | PubMed |
description | Artificial intelligence is one of the fastest-developing areas of science that covers a remarkably wide range of problems to be solved. It has found practical application in many areas of human activity, also in medicine. One of the directions of cooperation between computer science and medicine is to assist in diagnosing and proposing treatment methods with the use of IT tools. This study is the result of collaboration with the Children’s Memorial Health Institute in Warsaw, from where a database containing information about patients suffering from Bruton’s disease was made available. This is a rare disorder, difficult to detect in the first months of life. It is estimated that one in 70,000 to 90,000 children will develop Bruton’s disease. But even these few cases need detailed attention from doctors. Based on the data contained in the database, data mining was performed. During this process, knowledge was discovered that was presented in a way that is understandable to the user, in the form of decision trees. The best models obtained were used for the implementation of expert systems. Based on the data introduced by the user, the system conducts expertise and determines the severity of the course of the disease or the severity of the mutation. The CLIPS language was used for developing the expert system. Then, using this language, software was developed producing six expert systems. In the next step, experimental verification was performed, which confirmed the correctness of the developed systems. |
format | Online Article Text |
id | pubmed-8228842 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82288422021-06-26 Knowledge Discovery from Medical Data and Development of an Expert System in Immunology Pac, Małgorzata Mikutskaya, Irina Mulawka, Jan Entropy (Basel) Article Artificial intelligence is one of the fastest-developing areas of science that covers a remarkably wide range of problems to be solved. It has found practical application in many areas of human activity, also in medicine. One of the directions of cooperation between computer science and medicine is to assist in diagnosing and proposing treatment methods with the use of IT tools. This study is the result of collaboration with the Children’s Memorial Health Institute in Warsaw, from where a database containing information about patients suffering from Bruton’s disease was made available. This is a rare disorder, difficult to detect in the first months of life. It is estimated that one in 70,000 to 90,000 children will develop Bruton’s disease. But even these few cases need detailed attention from doctors. Based on the data contained in the database, data mining was performed. During this process, knowledge was discovered that was presented in a way that is understandable to the user, in the form of decision trees. The best models obtained were used for the implementation of expert systems. Based on the data introduced by the user, the system conducts expertise and determines the severity of the course of the disease or the severity of the mutation. The CLIPS language was used for developing the expert system. Then, using this language, software was developed producing six expert systems. In the next step, experimental verification was performed, which confirmed the correctness of the developed systems. MDPI 2021-05-31 /pmc/articles/PMC8228842/ /pubmed/34073080 http://dx.doi.org/10.3390/e23060695 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pac, Małgorzata Mikutskaya, Irina Mulawka, Jan Knowledge Discovery from Medical Data and Development of an Expert System in Immunology |
title | Knowledge Discovery from Medical Data and Development of an Expert System in Immunology |
title_full | Knowledge Discovery from Medical Data and Development of an Expert System in Immunology |
title_fullStr | Knowledge Discovery from Medical Data and Development of an Expert System in Immunology |
title_full_unstemmed | Knowledge Discovery from Medical Data and Development of an Expert System in Immunology |
title_short | Knowledge Discovery from Medical Data and Development of an Expert System in Immunology |
title_sort | knowledge discovery from medical data and development of an expert system in immunology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8228842/ https://www.ncbi.nlm.nih.gov/pubmed/34073080 http://dx.doi.org/10.3390/e23060695 |
work_keys_str_mv | AT pacmałgorzata knowledgediscoveryfrommedicaldataanddevelopmentofanexpertsysteminimmunology AT mikutskayairina knowledgediscoveryfrommedicaldataanddevelopmentofanexpertsysteminimmunology AT mulawkajan knowledgediscoveryfrommedicaldataanddevelopmentofanexpertsysteminimmunology |