DECODE: Data-driven machinE-learning aided stratification & management of multiple long-term COnditions in adults with intellectual disabilitiEs

What is the DECODE project?

DECODE is a newly funded study led by Loughborough University and the Leicestershire Partnership NHS Trust will develop AI based tools to improve the health and wellbeing of people with intellectual disabilities (also known as learning disabilities).

How is the DECODE project funded?

The DECODE project is a 30-month research project funded by the NIHR Artificial Intelligence for Multiple Long-Term Conditions (AIM) Programme.

Who is part of the DECODE team?

DECODE is led by Loughborough University (PI: Dr Gyuchan Thomas Jun, Reader in Socio-technical System Design) jointly with Leicestershire Partnership NHS Trust (joint PI: Dr Satheesh Gangadharan, Consultant Psychiatrist). Overall, the project team consists of fifteen co-investigators with expertise in the field of intellectual disabilities, neuropsychiatry, epidemiology, health data science, machine learning, data visualisation, human factors, qualitative research and ethics from eight institutions.

The co-investigators include Dr Georgina Cosma (AI and data science) and Dr Panos Balatsoukas (UX design) at Loughborough University, Dr Francesco Zaccardi (epidemiology), Dr Michelle O’Reilly (qualitative research) and Prof Kamlesh Khunti (primary care) at the University of Leicester, Ashley Akbari (data science) and Prof Simon Ellwood-Thompson (health informatics) at Swansea University, Dr Vasa Curcin (AI) at King’s College London, Prof  Rohit Shankar (neuropsychiatry) at the University of Plymouth, Dr Reza Kiani (intellectual disabilities) at Leicestershire Partnership NHS Trust,  Dr Neil Sinclair (ethics) at the University of Nottingham, Dr Chris Knifton (nursing) at De Montfort University, and Gillian Huddleston (PPI lead).

What AI-based tools will be implemented and why?

The project will develop machine learning approaches and tools to identify the clusters and trajectories of Multiple Long Term Conditions (MLTCs) in people with Intellectual Disabilities. The clusters will be utilised to develop approaches to combine multiple clinical guidelines relevant to the dominant/important clusters. User-friendly visualisations will present the outputs of AI analytics in a transparent, meaningful and trusted way to professionals, people with ID and carers. The clusters will also be utilised to develop actionable insights and AI usage scenarios for supporting the effective coordination of holistic care.

Dr Cosma is based at the department of Computer Science, and together with the project’s AI Research Associates who will be based in the same department, will lead and focus on the development of: machine learning approaches and tools to identify the clusters and trajectories of Multiple Long Term Conditions (MLTCs) in people with Intellectual Disabilities; tools utilising feature selection capabilities to identify key combinations of events in patient populations; development of personalised patient prediction models; and the implementation of methods to identify bias and develop strategies for mitigating and managing bias.