Enabling safe and rapid AI deployment at scale
Challenge
Leeds Teaching Hospitals NHS Trust (LTHT) was progressing AI initiatives across clinical workflows, from early pilots to planned evaluations. Every year, over 135,000 chest X-rays are performed at LTHT, many of which are crucial for urgent clinical decisions. The Trust needed a solution that would enable rapid evaluation, safe deployment, and central oversight of AI technologies within clinical systems, ensuring governance, clinical risk management, and alignment with patient safety requirements.
Solution
To address this, the Trust implemented Newton’s Tree, a vendor-neutral AI deployment and review platform. It enables NHS organisations to host AI tools securely while maintaining full visibility and control over clinical evaluations.
Using Newton’s Tree, LTHT supported structured evaluation of a chest X-ray AI tool, helping clinicians assess clinical safety and determine fitness for purpose. The AI solution is capable of identifying up to 85 different findings, including indicators of lung cancer, acute infections, and misplaced tubes, with results delivered within minutes. Clinicians were able to review AI outputs alongside their own assessments, ensuring alignment with clinical judgment before any consideration of deployment into live patient care.
“We’re proud to support Leeds in this important deployment. This is a strong example of how AI can be adopted responsibly and effectively when built around real clinical needs and backed by the right infrastructure. Our mission is to make AI easier to deploy, safer to use, and more valuable for both clinicians and patients across the NHS.”
Impact
The Newton’s Tree platform enabled LTHT to evaluate AI solutions safely and efficiently, providing a consistent environment for clinical review and oversight. Consultants and trainees used the AI review functionality to measure agreement between clinicians and the AI in identifying key findings, supporting the development of a clinical safety case. This structured evaluation ensures that AI-assisted diagnosis aligns closely with clinical judgment and helps accelerate patient care.
“This technology is about putting patients first. By helping busy frontline staff detect serious conditions quickly and accurately, this AI tool will support clinical decision-making and allow us to get patients the treatment they need faster. Such large-scale evaluations of the use of AI in everyday clinical practice should provide crucial information to inform our future use of AI to improve the quality of care that we provide to our patients.”
This structured, real-world evaluation demonstrates how AI can be assessed responsibly at scale within the NHS, ensuring patient safety, clinical oversight, and evidence-based practice remain central.
Find out more about this work in Newton’s Tree’s news story and watch their video.
