Pulmonary pathology
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No. 12 of 20
Getting Started with AI in Pulmonary Pathology
A practical primer for the practising pathologist — what the technology actually does in pulmonary pathology, what to ask of it, and how to start safely.
Pulmonary pathology divides cleanly for AI purposes. Thoracic oncology — lung carcinoma subtyping, biomarker assessment, staging — is a high-volume, well-funded, heavily studied domain. Interstitial lung disease is a low-volume, pattern-based, multidisciplinary domain where the pathologist’s contribution is one input among several.
What the primer covers
- SectionTwo distinct territories: thoracic oncology and interstitial lung disease
- SectionThoracic oncology: where the work has concentrated
- SectionInterstitial lung disease
- SectionYour first 90 days
- SectionValidation specifics
- SectionFailure modes to anticipate
- SectionWhat to watch next
- SectionKey references
Who it is for
- Pathologists in pulmonary 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.