DxGenerator: An Improved Differential Diagnosis Generator for Primary Care Based on MetaMap and Semantic Reasoning.
Journal
Methods of information in medicine
ISSN: 2511-705X
Titre abrégé: Methods Inf Med
Pays: Germany
ID NLM: 0210453
Informations de publication
Date de publication:
12 2022
12 2022
Historique:
pubmed:
21
7
2022
medline:
23
12
2022
entrez:
20
7
2022
Statut:
ppublish
Résumé
In recent years, researchers have used many computerized interventions to reduce medical errors, the third cause of death in developed countries. One of such interventions is using differential diagnosis generators in primary care, where physicians may encounter initial symptoms without any diagnostic presuppositions. These systems generate multiple diagnoses, ranked by their likelihood. As such, these reports' accuracy can be determined by the location of the correct diagnosis in the list. This study aimed to design and evaluate a novel practical web-based differential diagnosis generator solution in primary care. In this research, a new online clinical decision support system, called DxGenerator, was designed to improve diagnostic accuracy; to this end, an attempt was made to converge a semantic database with the unified medical language system (UMLS) knowledge base, using MetaMap tool and natural language processing. In this regard, 120 diseases of gastrointestinal organs causing abdominal pain were modeled into the database. After designing an inference engine and a pseudo-free-text interactive interface, 172 patient vignettes were inputted into DxGenerator and ISABEL, the most accurate similar system. The Wilcoxon signed ranked test was used to compare the position of correct diagnoses in DxGenerator and ISABEL. The α level was defined as 0.05. On a total of 172 vignettes, the mean and standard deviation of correct diagnosis positions improved from 4.2 ± 5.3 in ISABEL to 3.2 ± 3.9 in DxGenerator. This improvement was significant in the subgroup of uncommon diseases ( Using UMLS knowledge base and MetaMap Tools can improve the accuracy of diagnostic systems in which terms are entered in a free text manner. Applying these new methods will help the medical community accept medical diagnostic systems better.
Sections du résumé
BACKGROUND
In recent years, researchers have used many computerized interventions to reduce medical errors, the third cause of death in developed countries. One of such interventions is using differential diagnosis generators in primary care, where physicians may encounter initial symptoms without any diagnostic presuppositions. These systems generate multiple diagnoses, ranked by their likelihood. As such, these reports' accuracy can be determined by the location of the correct diagnosis in the list.
OBJECTIVE
This study aimed to design and evaluate a novel practical web-based differential diagnosis generator solution in primary care.
METHODS
In this research, a new online clinical decision support system, called DxGenerator, was designed to improve diagnostic accuracy; to this end, an attempt was made to converge a semantic database with the unified medical language system (UMLS) knowledge base, using MetaMap tool and natural language processing. In this regard, 120 diseases of gastrointestinal organs causing abdominal pain were modeled into the database. After designing an inference engine and a pseudo-free-text interactive interface, 172 patient vignettes were inputted into DxGenerator and ISABEL, the most accurate similar system. The Wilcoxon signed ranked test was used to compare the position of correct diagnoses in DxGenerator and ISABEL. The α level was defined as 0.05.
RESULTS
On a total of 172 vignettes, the mean and standard deviation of correct diagnosis positions improved from 4.2 ± 5.3 in ISABEL to 3.2 ± 3.9 in DxGenerator. This improvement was significant in the subgroup of uncommon diseases (
CONCLUSION
Using UMLS knowledge base and MetaMap Tools can improve the accuracy of diagnostic systems in which terms are entered in a free text manner. Applying these new methods will help the medical community accept medical diagnostic systems better.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
174-184Informations de copyright
Thieme. All rights reserved.
Déclaration de conflit d'intérêts
None declared.