Cardiovascular pathology
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No. 13 of 20
Getting Started with AI in Cardiovascular Pathology
A practical primer for the practising pathologist — what the technology actually does in cardiovascular pathology, what to ask of it, and how to start safely.
Cardiovascular pathology is low-volume in most departments, and much of its work is autopsy-based or highly specialised. But it contains one application that is close to ideal for machine learning: grading of cardiac allograft rejection on endomyocardial biopsy.
What the primer covers
- SectionA small subspecialty with one exceptionally well-suited task
- SectionThe task map
- SectionYour first 90 days
- SectionValidation specifics
- SectionFailure modes to anticipate
- SectionWhat to watch next
- SectionKey references
Who it is for
- Pathologists in cardiovascular pathology meeting diagnostic AI for the first time
- Laboratory leads assessing vendor claims and planning validation
- Trainees who want the regulatory and methodological context, not marketing
Educational guidance, not clinical protocol or regulatory advice. Algorithm authorisations and validation requirements change — confirm the current position with your regulator and your own quality system.