Machine and deep learning in inflammatory bowel disease.
Curr Opin Gastroenterol
; 39(4): 294-300, 2023 07 01.
Article
em En
| MEDLINE
| ID: mdl-37144491
ABSTRACT
PURPOSE OF REVIEW The Management of inflammatory bowel disease (IBD) has evolved with the introduction and widespread adoption of biologic agents; however, the advent of artificial intelligence technologies like machine learning and deep learning presents another watershed moment in IBD treatment. Interest in these methods in IBD research has increased over the past 10âyears, and they offer a promising path to better clinical outcomes for IBD patients. RECENT FINDINGS:
Developing new tools to evaluate IBD and inform clinical management is challenging because of the expansive volume of data and requisite manual interpretation of data. Recently, machine and deep learning models have been used to streamline diagnosis and evaluation of IBD by automating review of data from several diagnostic modalities with high accuracy. These methods decrease the amount of time that clinicians spend manually reviewing data to formulate an assessment.SUMMARY:
Interest in machine and deep learning is increasing in medicine, and these methods are poised to revolutionize the way that we treat IBD. Here, we highlight the recent advances in using these technologies to evaluate IBD and discuss the ways that they can be leveraged to improve clinical outcomes.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Doenças Inflamatórias Intestinais
/
Aprendizado Profundo
Tipo de estudo:
Guideline
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Curr Opin Gastroenterol
Assunto da revista:
GASTROENTEROLOGIA
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Estados Unidos