Kayser, 2019
Retamero, 2020, Complete digital pathology for routine histopathology diagnosis in a multicenter hospital network, Arch Pathol Lab Med, 144, 221, 10.5858/arpa.2018-0541-OA
Fraggetta, 2017, Routine digital pathology workflow: The Catania experience, J Pathol Inform, 8, 51, 10.4103/jpi.jpi_58_17
Vodovnik, 2018, Complete routine remote digital pathology services, J Pathol Inform, 9, 36, 10.4103/jpi.jpi_34_18
Griffin, 2017, Digital pathology in clinical use: Where are we now and what is holding us back?, Histopathology, 70, 134, 10.1111/his.12993
Haroske, 2018, “Digital Pathology in Diagnostics-reporting on digital images” guideline of the Professional Association of German Pathologists, Pathologe, 39, 250, 10.1007/s00292-018-0528-5
Hufnagl, 2018, Implementation of the “Digital Pathology in Diagnostics” guideline: Support systems and their functionality, Pathologe, 39, 222, 10.1007/s00292-018-0436-8
Bulten, 2020, Automated deep-learning system for Gleason grading of prostate cancer using biopsies: A diagnostic study, Lancet Oncol, 21, 233, 10.1016/S1470-2045(19)30739-9
Plancoulaine, 2015, A methodology for comprehensive breast cancer Ki67 labeling index with intra-tumor heterogeneity appraisal based on hexagonal tiling of digital image analysis data, Virchows Arch, 467, 711, 10.1007/s00428-015-1865-x
Polonia, 2020, Artificial intelligence improves the accuracy in histological classification of breast lesions, Am J Clin Pathol
Salto-Tellez, 2019, Artificial intelligence-the third revolution in pathology, Histopathology, 74, 372, 10.1111/his.13760
Pantanowitz, 2013, Lessons beyond barcoding: Lab automation and custom development, 69