Mascarenhas

et al., 2021

[43]

Portugal

53,555 images

CE images

CNN Model

The average sensitivities and specificities for automatically detecting various abnormalities were 87.8% ± 8.1% and 99.4% ± 3.7%, respectively.

Deep learning algorithms can detect and differentiate small bowel lesions with obvious bleeding potential.

Ungaro

et al., 2020

[44]

United States

265 patients with an average age of 11.6 years

Protein and serologic markers

Multivariate Cox regression model

For B2 (stricturing) complications, four proteins (IL7, MMP10, IL12B, CCL11) and two serologic markers (LnASCA IgA, LnCbir) were selected as the most predictive. For B3 (penetrating) complications, five proteins (TNFSF14, CCL4, IL15RA, TNFB, CD40) and three serologic markers (LnASCA IgA, LnANCA, LnCbir) were selected as the most predictive for B3.

Different proteins have better predictive value for diagnosing different complications of pediatric Crohn’s disease, B2 and B3.

Colorectal Cancer

Kudo

et al., 2020

[46]

Japan

69,142 images

WLI images, EC-NBI images, and stained EC images

EndoBRAIN CAD system

In stained images: EndoBRAIN achieved an accuracy of 98% (97.3 - 98.6). In NBI images: EndoBRAIN achieved an accuracy of 94.6%.

EndoBRAIN improved the accuracy and sensitivity of endoscopists in both stained and NBI modes.