Compare use cases

Drop two or three slugs into the URL — for example ?slugs=demo-mia-breast-screening,demo-idx-dr-retinopathy — or pick from the validated catalogue below.

Pick from validated:

AI imaging triage for the acute stroke pathway AI second reader for breast cancer screening Autonomous diabetic retinopathy screening in primary care Pre-operative risk-stratification model for major surgery Self-referral assistant for NHS Talking Therapies Type-2 diabetes long-term outcome predictor

Clear selection

	Autonomous diabetic retinopathy screening in primary care Netherlands	Self-referral assistant for NHS Talking Therapies United Kingdom	AI imaging triage for the acute stroke pathway United Kingdom
Trust badge	Validated	Validated	Validated & replicable
Evidence strength	Robust evidence	Developing evidence	Developing evidence
Pipeline stage	Validated	Validated	Scaled
Intended use	Provides an autonomous screening decision for more-than-mild diabetic retinopathy from retinal fundus images, referring positive cases to ophthalmology.	Supports patient self-referral by collecting clinical information conversationally and routing referrals, reducing administrative wait time.	Interprets acute stroke imaging to support rapid identification of large-vessel occlusion and treatment eligibility, accelerating thrombectomy referral.
Specialty	Other	Psychiatry	Emergency medicine
Autonomy	Autonomous (acts without a human)	Human in the loop (human acts)	Informs a human (advisory)
Deployment	Active deployment	Active deployment	Scaling up
EU AI Act tier	High-risk	Limited risk	High-risk
EU MDR class	Class IIb	Not a device	Class IIb
CE marking	CE marked	Not required	CE marked
NICE ESF tier	Tier C — treat / diagnose / calculate risk	Tier B — inform / monitor	Tier C — treat / diagnose / calculate risk
Headline metric	Sensitivity: 0.87	Accuracy: 0.93	Time saved: 60
Subgroup assessed	Yes	Yes	Yes