Is Your AI Tool Clinically Ready?
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By
February 9, 2026
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10 min
Bobbi Pritt, Chair of Clinical Microbiology at Mayo Clinic, elaborates on the transformative impact of AI in pathology, particularly in image-based diagnostics. AI excels in repetitive and measurable tasks, enhancing efficiency by reducing review time for negative specimens significantly. Its potential spans automated workflow processes and malignancy detection as a supportive tool. Pathologists are encouraged to define clinical needs that drive innovation in AI development while ensuring training for future professionals on leveraging AI responsibly.
1. AI enhances efficiency in image-based pathology. 2. It supports tasks like counting mitotic figures and quality control. 3. AI saves time in slide reviews, focusing on positive cases. 4. Proper evaluation criteria for AI readiness include validation and evidence. 5. Pathologists must define clinical needs that guide AI development. 6. Trainees should understand AI's tools and implications. 7. Emphasis on augmented intelligence rather than total replacement of human expertise. 8. AI's role in microbiology includes interpreting complex datasets and optimizing workflows.
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