Applications of Artificial Intelligence to Eosinophilic Esophagitis

Eric Reuben Smith; Jay Shah

doi:10.3390/gastroent13030022

Applications of Artificial Intelligence to Eosinophilic Esophagitis

Eric Reuben Smith, Jay Shah

Producción científica: Review article › revisión exhaustiva

2 Citas (Scopus)

Resumen

Eosinophilic Esophagitis (EoE) is a chronic immune-related inflammation, and challenges to its diagnosis and treatment evaluation persist. This literature review evaluates all AI applications to EOE, including 15 studies using AI algorithms for counting eosinophils in biopsies, as well as newer diagnostics using mRNA transcripts in biopsies, endoscopic photos, blood and urine biomarkers, and an improved scoring system for disease classification. We also discuss the clinical impact of these models, challenges faced in applying AI to EoE, and future applications. In conclusion, AI has the potential to improve diagnostics and clinical evaluation in EoE, improving patient outcomes.

Idioma original	English (US)
Páginas (desde-hasta)	218-227
Número de páginas	10
Publicación	Gastroenterology Insights
Volumen	13
N.º	3
DOI	https://doi.org/10.3390/gastroent13030022
Estado	Published - sept 2022
Publicado de forma externa	Sí

ASJC Scopus subject areas

Hepatology
Gastroenterology

Acceder al documento

10.3390/gastroent13030022

Otros archivos y enlaces

Citar esto

@article{437b0660eb1443abb115a8f215a479ba,

title = "Applications of Artificial Intelligence to Eosinophilic Esophagitis",

abstract = "Eosinophilic Esophagitis (EoE) is a chronic immune-related inflammation, and challenges to its diagnosis and treatment evaluation persist. This literature review evaluates all AI applications to EOE, including 15 studies using AI algorithms for counting eosinophils in biopsies, as well as newer diagnostics using mRNA transcripts in biopsies, endoscopic photos, blood and urine biomarkers, and an improved scoring system for disease classification. We also discuss the clinical impact of these models, challenges faced in applying AI to EoE, and future applications. In conclusion, AI has the potential to improve diagnostics and clinical evaluation in EoE, improving patient outcomes.",

keywords = "artificial intelligence, eosinophilic esophagitis, machine learning",

author = "Smith, {Eric Reuben} and Jay Shah",

note = "Publisher Copyright: {\textcopyright} 2022 by the authors. Licensee MDPI, Basel, Switzerland.",

year = "2022",

month = sep,

doi = "10.3390/gastroent13030022",

language = "English (US)",

volume = "13",

pages = "218--227",

journal = "Gastroenterology Insights",

issn = "2036-7422",

publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",

number = "3",

}

TY - JOUR

T1 - Applications of Artificial Intelligence to Eosinophilic Esophagitis

AU - Smith, Eric Reuben

AU - Shah, Jay

PY - 2022/9

Y1 - 2022/9

N2 - Eosinophilic Esophagitis (EoE) is a chronic immune-related inflammation, and challenges to its diagnosis and treatment evaluation persist. This literature review evaluates all AI applications to EOE, including 15 studies using AI algorithms for counting eosinophils in biopsies, as well as newer diagnostics using mRNA transcripts in biopsies, endoscopic photos, blood and urine biomarkers, and an improved scoring system for disease classification. We also discuss the clinical impact of these models, challenges faced in applying AI to EoE, and future applications. In conclusion, AI has the potential to improve diagnostics and clinical evaluation in EoE, improving patient outcomes.

AB - Eosinophilic Esophagitis (EoE) is a chronic immune-related inflammation, and challenges to its diagnosis and treatment evaluation persist. This literature review evaluates all AI applications to EOE, including 15 studies using AI algorithms for counting eosinophils in biopsies, as well as newer diagnostics using mRNA transcripts in biopsies, endoscopic photos, blood and urine biomarkers, and an improved scoring system for disease classification. We also discuss the clinical impact of these models, challenges faced in applying AI to EoE, and future applications. In conclusion, AI has the potential to improve diagnostics and clinical evaluation in EoE, improving patient outcomes.

KW - artificial intelligence

KW - eosinophilic esophagitis

KW - machine learning

UR - http://www.scopus.com/inward/record.url?scp=85134511478&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85134511478&partnerID=8YFLogxK

U2 - 10.3390/gastroent13030022

DO - 10.3390/gastroent13030022

M3 - Review article

AN - SCOPUS:85134511478

SN - 2036-7422

VL - 13

SP - 218

EP - 227

JO - Gastroenterology Insights

JF - Gastroenterology Insights

IS - 3

ER -

Applications of Artificial Intelligence to Eosinophilic Esophagitis

Resumen

ASJC Scopus subject areas

Acceder al documento

Otros archivos y enlaces

Huella

Citar esto