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Computer-aided/AI-driven tools are increasing being developed for use with digital pathology images. Whether a given scheme makes it into clinical use depends on a multitude of factors, perhaps most importantly whether it has an impact on a clinician’s decision-making process thus on patient care and outcomes. To have a positive impact, clinical decision support tools must be well-integrated into routine clinical workflows and thus require assessment from a human factors perspective that includes attention to ways these tools impact users’ perceptual and cognitive information processing mechanisms. Methods from implementation sciences (the scientific study of methods to promote systematic uptake of research findings and other evidence-based practices into routine practice to improve the quality and effectiveness of health services) can also be used to prepare users for and then assess the impact of introducing these tools into the clinical workflow. This paper will provide an overview of these perspectives, drawing on the history of medical image perception research in radiology and the growing application of these principles and methods in pathology.
Elizabeth A. Krupinski
"Translating computational innovations into reality: focus on the users!", Proc. SPIE 12471, Medical Imaging 2023: Digital and Computational Pathology, 124710S (6 April 2023); https://doi.org/10.1117/12.2663067
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Elizabeth A. Krupinski, "Translating computational innovations into reality: focus on the users!," Proc. SPIE 12471, Medical Imaging 2023: Digital and Computational Pathology, 124710S (6 April 2023); https://doi.org/10.1117/12.2663067