1. Pathologists' Computer-Assisted Diagnosis.
- Author
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Farahani, Navid, Zheng Liu, Jutt, Dylan, and Fine, Jeffrey L.
- Subjects
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ARTIFICIAL intelligence , *AUTOMATION , *COLLECTION & preservation of biological specimens , *BREAST tumors , *PATHOLOGISTS , *SYSTEMS design , *WORKFLOW , *VIRTUAL microscopy , *COMPUTER-aided diagnosis - Abstract
Context.--Pathologists' computer-assisted diagnosis (pCAD) is a proposed framework for alleviating challenges through the automation of their routine sign-out work. Currently, hypothetical pCAD is based on a triad of advanced image analysis, deep integration with heterogeneous information systems, and a concrete understanding of traditional pathology workflow. Prototyping is an established method for designing complex new computer systems such as pCAD. Objective.--To describe, in detail, a prototype of pCAD for the sign-out of a breast cancer specimen. Design.--Deidentified glass slides and data from breast cancer specimens were used. Slides were digitized into whole-slide images with an Aperio ScanScope XT, and screen captures were created by using vendor-provided software. The advanced workflow prototype was constructed by using PowerPoint software. Results.--We modeled an interactive, computer-assisted workflow: pCAD previews whole-slide images in the context of integrated, disparate data and predefined diagnostic tasks and subtasks. Relevant regions of interest (ROIs) would be automatically identified and triaged by the computer. A pathologist's sign-out work would consist of an interactive review of important ROIs, driven by required diagnostic tasks. The interactive session would generate a pathology report automatically. Conclusions.--Using animations and real ROIs, the pCAD prototype demonstrates the hypothetical sign-out in a stepwise fashion, illustrating various interactions and explaining how steps can be automated. The file is publicly available and should be widely compatible. This mock-up is intended to spur discussion and to help usher in the next era of digitization for pathologists by providing desperately needed and long-awaited automation. [ABSTRACT FROM AUTHOR]
- Published
- 2017
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