Artificial Intelligence in the Diagnosis of Invasive Mold Infection: Development of an Automated Histologic Identification System to Distinguish Between <i>Aspergillus</i> and Mucorales
Author:
Affiliation:
1. Department of Surgical Pathology, Faculty of Medicine, Toho University
2. Department of Chemotherapy and Mycoses, National Institute of Infectious Diseases
Publisher
The Japanese Society for Medical Mycology
Subject
Infectious Diseases,Microbiology
Link
https://www.jstage.jst.go.jp/article/mmj/63/4/63_22-00013/_pdf
Reference12 articles.
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2. 2) Okubo Y, Ishiwatari T, Izumi H, Sato F, Aki K, Sasai D, Ando T, Shinozaki M, Natori K, Tochigi N, Wakayama M, Hata Y, Nakayama H, Nemoto T, Shibuya K: Pathophysiological implication of reversed CT halo sign in invasive pulmonary mucormycosis: a rare case report. Diagn Pathol 8: 82, 2013.
3. 3) Shinozaki M, Tochigi N, Sadamoto S, Yamagata Murayama S, Wakayama M, Nemoto T: Histopathological diagnosis of invasive fungal infections in formalin-fixed and paraffin-embedded tissues in conjunction with molecular methods: comparison of reproducibility and reliability of histopathological evaluation, polymerase chain reaction, and in situ hybridization. Med Mycol J 59: E7–E18, 2018.
4. 4) Sadamoto S, Shinozaki M, Nagi M, Nihonyanagi Y, Ejima K, Mitsuda A, Wakayama M, Tochigi N, Murakami Y, Hishima T, Nemoto T, Nakamura S, Miyazaki Y, Shibuya K: Histopathological study on the prevalence of trichosporonosis in formalin-fixed and paraffin-embedded tissue autopsy sections by in situ hybridization with peptide nucleic acid probe. Med Mycol 58: 460–468, 2020.
5. 5) Tochigi N, Sadamoto S, Shinozaki M, Wakayama M, Shibuya K: Comparison in quantities from including angles comprising lines of hypha themselves in histological images between Mucorales and Aspergillus. Med Mycol J 60: 85–89, 2019.
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