Case Studies


MRI Imaging Analytics for Prostate Cancer

Prostate cancer is set to become the most common cancer in men with approximately 50,000 new cases every year. Subjectivity in diagnosis is a known issue with sensitivity recorded as low as 57%. A high time and economic cost of biopsy complications mean that radiologists are under increasing pressure to improve efficiency. is set to become the first AI-based solution trained on 1000s of MRI scans from a variety of sources. The trained kernel is currently undergoing clinical investigation. We are currently operating at a sensitivity of 94% and specificity of 90%.

Bone Fracture Diagnosis

Doctors in A&E are overworked, tired and pressured – they need every bit of help they can get. Moreover junior staff can have an error rate of up to 30% in identifying fractures from scans. has teamed up with Robert Gordon University via an SBRI grant to deliver an automated tool to diagnose fractures quickly and efficiently. The AI solutions were built on hundreds of x-ray images of wrist and collar bone breaks – indications that could easily be missed in a busy A&E department by junior doctors.

Waiting List Stratification

NHS waiting lists are at an all time high. is being used to better risk stratify the waiting lists, using primary, secondary care data points as well as clinician and patient wishes.

Clinical Trial Optimisation

Expensive clinical trials can fail due to patient non-compliance with clinical trial guidelines. is using personality data to see which traits are most likely to comply with medication protocol.

ID-Liver is the AI partner to the large InnovateUK funded ID Liver project (earlier detection of Liver Disease) a collaboration with Manchester University, Roche and GE healthcare. Early results are strongly positive where is able to diagnose the disease 6% better than current standard of care.

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