Bias often hides in your training data. . Control for scanner type, staining variability, and source institution. Robust AI starts with representative input. #DigitalPathology #AIValidation #BiasInAI #ComputationalPathology ------------------------------------------------- Pohlmeyer-Esch G, Halsey C, Boisclair J, et al. Digital Pathology and Artificial Intelligence Applied to Nonclinical Toxicology Pathology: ”The Current State, Challenges, and Future Directions. Toxicologic Pathology. 2025;53(3
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Bias often hides in your training data. . Control for scanner type, st…
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TikTokdigitalpathology
Deploying digital pathology isn’t about buying a tool —it’s about leading a transformation. And where many projects struggle isn’t technology, but mindset and context. Digital pathology changes workflows, roles, regulations, and ultimately patient care. Validation isn’t just about performance metrics —it’s about intended use, clinical fit, and how real people actually work with the system. There’s no universal playbook either, because academic centers, community hospitals, and distributed teams
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