Deep learning in gastric tissue diseases: a systematic review

Wanderson Gonçalves e Gonçalves, Marcelo Henrique de Paula dos Santos, Fábio Manoel França Lobato, Ândrea Ribeiro-dos-Santos, Gilderlanio Santana de Araújo
2020 BMJ Open Gastroenterology  
BackgroundIn recent years, deep learning has gained remarkable attention in medical image analysis due to its capacity to provide results comparable to specialists and, in some cases, surpass them. Despite the emergence of deep learning research on gastric tissues diseases, few intensive reviews are addressing this topic.MethodWe performed a systematic review related to applications of deep learning in gastric tissue disease analysis by digital histology, endoscopy and radiology
more » ... nsThis review highlighted the high potential and shortcomings in deep learning research studies applied to gastric cancer, ulcer, gastritis and non-malignant diseases. Our results demonstrate the effectiveness of gastric tissue analysis by deep learning applications. Moreover, we also identified gaps of evaluation metrics, and image collection availability, therefore, impacting experimental reproducibility.
doi:10.1136/bmjgast-2019-000371 pmid:32337060 pmcid:PMC7170401 fatcat:tmlxfjmdmrht3aa2yvyotguvuy