Is Your AI Tool Clinically Ready?
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By
February 9, 2026
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10 min
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1
AI enhances efficiency in image-based pathology.
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2
It supports tasks like counting mitotic figures and quality control.
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3
AI saves time in slide reviews, focusing on positive cases.
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4
Proper evaluation criteria for AI readiness include validation and evidence.
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5
Pathologists must define clinical needs that guide AI development.
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6
Trainees should understand AI's tools and implications.
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Emphasis on augmented intelligence rather than total replacement of human expertise.
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8
AI's role in microbiology includes interpreting complex datasets and optimizing workflows.
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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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