Clinical chemistry
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No. 19 of 20
Getting Started with AI in Clinical Chemistry and Laboratory Medicine
A practical primer for the practising pathologist — what the technology actually does in clinical chemistry, what to ask of it, and how to start safely.
Clinical chemistry generates more discrete results than every other laboratory discipline combined. A single hospital laboratory produces millions of numeric results annually, each timestamped, each linked to a patient record, most with longitudinal history. This is the richest structured dataset in medicine, and it requires no scanning, no annotation and no image acquisition to use.
What the primer covers
- SectionThe discipline where AI has the most data and the least visibility
- SectionAutoverification: the flagship application
- 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 clinical chemistry 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.