Open AccessUse of digital pathology and artificial intelligence for the diagnosis of Helicobacter pylori in gastric biopsies
Author(s) -
Daniel S. Liscia,
Mariangela D’Andrea,
Elena Biletta,
Donata Bellis,
Kejsi Demo,
Franco Ferrero,
Alberto Petti,
Roberto Butinar,
Enzo D’Andrea,
Giuditta Davini
Publication year - 2022
Publication title -
pathologica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.243
H-Index - 18
eISSN - 1591-951X
pISSN - 0031-2983
DOI - 10.32074/1591-951x-751
Subject(s) - false positive paradox , virtual microscopy , helicobacter pylori , magnification , artificial intelligence , digital pathology , gold standard (test) , stain , medicine , computer science , biopsy , telepathology , pathology , radiology , gastroenterology , staining , health care , telemedicine , economics , economic growth
A common source of concern about digital pathology (DP) is that limited resolution could be a reason for an increased risk of malpractice. A frequent question being raised about this technology is whether it can be used to reliably detect Helicobacter pylori (HP) in gastric biopsies, which can be a significant burden in routine work. The main goal of this work is to show that a reliable diagnosis of HP infection can be made by DP even at low magnification. The secondary goal is to demonstrate that artificial intelligence (AI) algorithms can diagnose HP infections on virtual slides with sufficient accuracy.