APPLICATION OF THE WORD2VEC ALGORITHM FOR CLINICAL DIAGNOSIS DETERMINATION

The article examines the use of Natural Language Processing technologies in modern medicine for knowledge acquisition and the implementation of decisionmaking methods. The application of information technology in healthcare has become one of the main requirements of the modern era. Enhancing th...

Full description

Saved in:
Bibliographic Details
Main Author: Uzeyir Gurbanli
Format: Article
Language:English
Published: Information Technology Publishing House 2025-02-01
Series:Problems of Information Society
Online Access:https://jpis.az/uploads/article/en/2025_1/APPLICATION_OF_THE_WORD2VEC_ALGORITHM_FOR_CLINICAL_DIAGNOSIS_DETERMINATION.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850037317055545344
author Uzeyir Gurbanli
author_facet Uzeyir Gurbanli
author_sort Uzeyir Gurbanli
collection DOAJ
description The article examines the use of Natural Language Processing technologies in modern medicine for knowledge acquisition and the implementation of decisionmaking methods. The application of information technology in healthcare has become one of the main requirements of the modern era. Enhancing the quality and accessibility of medical services necessitates the utilization of modern technologies, mathematical methods, and the capabilities of artificial intelligence, alongside the development of comprehensive information systems. The paper proposes methods for analyzing and applying tools to assist physicians in diagnosing conditions and determining treatment plans with the help of artificial intelligence. It also focuses on evaluating the quality of diagnostic and treatment processes through applıcation of different methods and practical application. The analysis of large volumes of medical data using Natural Language Processing technology enables the extraction of valuable insights. A significant portion of medical data is stored and exchanged in text form compliant with the Health Level Seven standard, making semantic similarity methods that operate on textual data highly effective in this domain. By designing and implementing rules for applying and integrating different algorithms, it is possible to transform medical data into valuable knowledge, contributing significantly to advancements in the medical field. The article presents a Word2Vec algorithm-based approach for detecting diagnoses of cardiovascular diseases from collected patient histories, as well as refining existing diagnoses. The development of an algorithm capable of assigning new diagnoses based on historical patient records constitutes one of the key outcomes of this research.
format Article
id doaj-art-47083e46ecdf4a2385fe854d543d3cc0
institution DOAJ
issn 2077-964X
2309-7566
language English
publishDate 2025-02-01
publisher Information Technology Publishing House
record_format Article
series Problems of Information Society
spelling doaj-art-47083e46ecdf4a2385fe854d543d3cc02025-08-20T02:56:54ZengInformation Technology Publishing HouseProblems of Information Society2077-964X2309-75662025-02-01161263310.25045/jpis.v16.i1.03APPLICATION OF THE WORD2VEC ALGORITHM FOR CLINICAL DIAGNOSIS DETERMINATIONUzeyir Gurbanli The article examines the use of Natural Language Processing technologies in modern medicine for knowledge acquisition and the implementation of decisionmaking methods. The application of information technology in healthcare has become one of the main requirements of the modern era. Enhancing the quality and accessibility of medical services necessitates the utilization of modern technologies, mathematical methods, and the capabilities of artificial intelligence, alongside the development of comprehensive information systems. The paper proposes methods for analyzing and applying tools to assist physicians in diagnosing conditions and determining treatment plans with the help of artificial intelligence. It also focuses on evaluating the quality of diagnostic and treatment processes through applıcation of different methods and practical application. The analysis of large volumes of medical data using Natural Language Processing technology enables the extraction of valuable insights. A significant portion of medical data is stored and exchanged in text form compliant with the Health Level Seven standard, making semantic similarity methods that operate on textual data highly effective in this domain. By designing and implementing rules for applying and integrating different algorithms, it is possible to transform medical data into valuable knowledge, contributing significantly to advancements in the medical field. The article presents a Word2Vec algorithm-based approach for detecting diagnoses of cardiovascular diseases from collected patient histories, as well as refining existing diagnoses. The development of an algorithm capable of assigning new diagnoses based on historical patient records constitutes one of the key outcomes of this research.https://jpis.az/uploads/article/en/2025_1/APPLICATION_OF_THE_WORD2VEC_ALGORITHM_FOR_CLINICAL_DIAGNOSIS_DETERMINATION.pdf
spellingShingle Uzeyir Gurbanli
APPLICATION OF THE WORD2VEC ALGORITHM FOR CLINICAL DIAGNOSIS DETERMINATION
Problems of Information Society
title APPLICATION OF THE WORD2VEC ALGORITHM FOR CLINICAL DIAGNOSIS DETERMINATION
title_full APPLICATION OF THE WORD2VEC ALGORITHM FOR CLINICAL DIAGNOSIS DETERMINATION
title_fullStr APPLICATION OF THE WORD2VEC ALGORITHM FOR CLINICAL DIAGNOSIS DETERMINATION
title_full_unstemmed APPLICATION OF THE WORD2VEC ALGORITHM FOR CLINICAL DIAGNOSIS DETERMINATION
title_short APPLICATION OF THE WORD2VEC ALGORITHM FOR CLINICAL DIAGNOSIS DETERMINATION
title_sort application of the word2vec algorithm for clinical diagnosis determination
url https://jpis.az/uploads/article/en/2025_1/APPLICATION_OF_THE_WORD2VEC_ALGORITHM_FOR_CLINICAL_DIAGNOSIS_DETERMINATION.pdf
work_keys_str_mv AT uzeyirgurbanli applicationoftheword2vecalgorithmforclinicaldiagnosisdetermination