Genevieve McArthur, Philippa M Eve, Kristy Jones, Erin Banales, Saskia Kohnen, Thushara Anandakumar, Linda Larsen, Eva Marinus, Hua-Chen Wang, Anne Castles
Phonics training for English-speaking poor readers
The Cochrane database of systematic reviews
evaluation morphologic features inflammation gastric atrophy intestinal metaplasia crucial diagnosing gastritis however artificial intelligence analysis nontumor diseases like gastritis limited previous deep learning models omitted important morphologic indicators cannot simultaneously diagnose gastritis indicators provide interpretable labels address attentionbased multiinstance multilabel learning network ammnet developed simultaneously achieve multilabel diagnosis activity atrophy intestinal metaplasia slidelevel weak labels evaluate ammnets realworld performance diagnostic test designed observe improvements junior pathologists diagnostic accuracy efficiency without ammnet assistance study 1096 patients seven independent medical centers ammnet performed well assessing activity area curve auc 093 atrophy auc 097 intestinal metaplasia auc 093 falsenegative rates indicators 004 008 018 respectively junior pathologists lower falsenegative rates model assistance 015 versus 010 furthermore ammnet reduced time required per whole slide image 546 285 minutes enhancing diagnostic efficiency blocklevel clustering analysis ammnet effectively visualized taskrelated patches within whole slide images improving interpretability findings highlight ammnets effectiveness accurately evaluating gastritis morphologic indicators multicenter data sets using multiinstance multilabel learning strategies support routine diagnostic pathology deserves evaluation