The emerging role of artificial intelligence in the reporting of prostate pathology

Affiliations

¹ Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden. Electronic address: lars.egevad@ki.se.
² Department of Pathology and Molecular Medicine, Wellington School of Medicine and Health Sciences, University of Otago, Wellington, New Zealand.
³ Aquesta Uropathology and University of Queensland, Brisbane, Qld, Australia.
⁴ Department of Surgical Pathology, Aichi Medical University, School of Medicine, Nagoya, Japan.
⁵ Pathology Informatics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.
⁶ Wesley Urology Clinic, Brisbane, Qld, Australia.
⁷ Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Institute of Biomedicine, University of Turku, Turku, Finland.
⁸ Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
⁹ Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Editorial

Lars Egevad et al. Pathology. 2021 Aug.

. 2021 Aug;53(5):565-567.

doi: 10.1016/j.pathol.2021.04.002. Epub 2021 Jun 6.

¹ Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden. Electronic address: lars.egevad@ki.se.
² Department of Pathology and Molecular Medicine, Wellington School of Medicine and Health Sciences, University of Otago, Wellington, New Zealand.
³ Aquesta Uropathology and University of Queensland, Brisbane, Qld, Australia.
⁴ Department of Surgical Pathology, Aichi Medical University, School of Medicine, Nagoya, Japan.
⁵ Pathology Informatics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.
⁶ Wesley Urology Clinic, Brisbane, Qld, Australia.
⁷ Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Institute of Biomedicine, University of Turku, Turku, Finland.
⁸ Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
⁹ Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

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Comment on

Automated acquisition of explainable knowledge from unannotated histopathology images.
Yamamoto Y, Tsuzuki T, Akatsuka J, Ueki M, Morikawa H, Numata Y, Takahara T, Tsuyuki T, Tsutsumi K, Nakazawa R, Shimizu A, Maeda I, Tsuchiya S, Kanno H, Kondo Y, Fukumoto M, Tamiya G, Ueda N, Kimura G. Yamamoto Y, et al. Nat Commun. 2019 Dec 18;10(1):5642. doi: 10.1038/s41467-019-13647-8. Nat Commun. 2019. PMID: 31852890 Free PMC article.