Delivering impact: programmes and projects
AI technology provides the opportunity to target diverse clinical pathways, from head to toe, in early life and old age.
The AI Centre is delivering a number of key functions as part of national programmes and projects across multiple domains.
One London Secure Data environment (SDE)
London aims to be the healthiest global city and a leading hub for Life Sciences & Digital Health – aligned with the Mayor’s Growth Plan and UK Industrial Strategy.
The vision is to establish a London Health Innovation Zone as a globally leading ecosystem where the city’s deep, diverse health data is securely accessed and used at scale; and where industry partners can access innovation support to develop and adopt products and services that tackle real-world health challenges.
The AI Centre had been commissioned as a key delivery mechanism for enhanced analytics functionality for the London Secure Data Environment, including developing a set of tools and platforms for all 5 London ICBs to enable predictive analytics and data science capabilities for population Health intervention, research and innovation.
Population Health Data science
Within our role in One London, we are working with London’s ICBs to deepening level of insights from data, while aligning to local requirements.
We are Sharing and “porting” a central library of code, tooling, and predictive analytics models, for local adaptation and use across organisational boundaries: ‘Infrastructure-as-Code’.
Learning Health Systems:
As part of this work – we developed detailed segmentation model, with more than 60 definitions of clinical conditions, complications, and measurements, in primary and secondary care. Used to construct a descriptive, geo-spatial profile of comorbidity and resource utilisation across neighbourhood team, GPs and hospitals.
We are building an interactive live dashboard tool - PRISM = Personalised Risk, Intelligent Stratification and Modelling, demo video of PRISM.
We are working with SEL ICB and other London ICBs on priority ML models for: falls prediction; complex long-term conditions pathway; comorbidity; pediatrics diabetes progression, frailty and more.
Previously, we developed AI technologies for medical imaging delivery, interpretation, and reporting in MRI, CT, PET, and ultrasound scans. These research projects enabled applications that enable faster and earlier diagnosis, automation of reporting, improved patient screening for disease, and personalised therapies. Link to previous projects