Gynaecological pathology
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No. 9 of 20
Getting Started with AI in Gynaecological Pathology
A practical primer for the practising pathologist — what the technology actually does in gynaecological pathology, what to ask of it, and how to start safely.
Gynaecological pathology contains two AI opportunities with almost nothing in common. The first is cervical screening, the oldest and most heavily validated application in the entire discipline. The second is endometrial and ovarian carcinoma classification, where the field is being reorganised around molecular categories and where AI’s role is to infer those categories from morphology.
What the primer covers
- SectionA subspecialty split between screening and molecular classification
- SectionCervical: the strongest evidence base in pathology
- SectionEndometrial carcinoma: morphology inferring molecule
- SectionOvarian and other tasks
- SectionYour first 90 days
- SectionValidation specifics
- SectionFailure modes to anticipate
- SectionWhat to watch next
- SectionKey references
Who it is for
- Pathologists in gynaecological 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.