The 18 use case families

AI that detects or characterises disease from medical images or pathology specimens.

AI that supports clinicians with diagnostic or treatment decisions at the point of care.

AI that predicts the risk of a future clinical event for individuals or cohorts.

AI that supports planning, guidance, or outcome prediction across the surgical pathway.

AI that improves the safety and appropriateness of prescribing and medication management.

AI that interprets genomic or molecular data to personalise diagnosis and treatment.

AI that screens for or assesses mental health and neuro-cognitive conditions.

AI supporting remote monitoring, self-management, and escalation for chronic conditions.

AI that continuously analyses inpatient physiological data to detect deterioration.

AI that optimises scheduling, capacity, and resource allocation in healthcare operations.

AI that automates documentation, coding, and administrative back-office processes.

AI that optimises transitions of care and multi-disciplinary coordination.

AI that communicates with and educates patients to support engagement and adherence.

AI for surveillance, outbreak prediction, and population-level health modelling.

AI that supports dispatch, emergency department flow, and time-critical pathways.

AI that assesses and supports rehabilitation and allied health interventions.

AI that accelerates clinical research, trial design, and recruitment.

AI that optimises medical supply chains, inventory, and asset maintenance.