Can artificial intelligence improve the diagnosis and management of patients with eosinophilic esophagitis?

Table 2 Summary of artificial intelligence methodologies applicable to eosinophilic esophagitis diagnosis

AI methodology	Description	Applications in EoE
Supervised ML	Algorithms that rely on labeled training data to learn and predict outcomes	Classifying endoscopic images, predicting eosinophil counts
DL	Subset of ML utilizing neural networks for pattern recognition	Analyzing endoscopic and histopathological data
Convolutional neural networks	Special type of DL particularly adept at image recognition	Enhancing diagnostic accuracy in endoscopic images
Random decision forest	ML algorithm combining multiple data sources for improved decision making	Integrating clinical and endoscopic data for diagnosis
Natural language processing	AI field focused on interaction between computers and human language	Analyzing electronic health records for diagnostic insights

AI: Artificial intelligence; EoE: Eosinophilic esophagitis; ML: Machine learning; DL: Deep learning.