A new AI platform is set to aid in the early detection of rheumatic and musculoskeletal diseases.

A team led by Henley Business School, University of Reading, has secured a £1.2 million grant for the development of RMD-Health.

This machine learning system aims to enhance the early detection and referral of rheumatic and musculoskeletal diseases (RMD).

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The project will be piloted at the Royal Berkshire NHS Foundation Trust (RBFT) and Oxford University Hospitals NHS Foundation Trust (OUH) over the next three years.

The initiative is partially funded by the National Institute for Health and Care Research (NIHR) and will focus on preparing the product for regulatory approval and commercial use.

Rheumatic and musculoskeletal diseases affect up to a third of the UK population and are leading causes of disability, including inflammatory arthritis, and one of the biggest contributors to sick days and unemployment.

Professor Weizi Li, the project's lead and Professor of Informatics and Digital Health at Henley, said: "With an estimated annual cost of £1.8 billion in sick leave and work-related disability for rheumatoid arthritis alone, the current RMD referral system faces huge challenges."

The new machine learning system is designed to help doctors refer patients more accurately and quickly, leading to faster and more effective treatment.

Between 2019 and 2021, general practitioners had only 40 per cent accuracy in suspected early inflammatory arthritis referrals.

This also led to delays in patients accessing the correct clinics and treatments, often resulting in multiple consultations with GPs.

Dr Antoni Chan, project co-lead and Consultant Rheumatologist and Physician at RBFT, added: "This exciting and innovative project represents a major step forward in the early detection and referral of RMD, promising improved patient outcomes, reduced healthcare costs and increased efficiency across our healthcare system."

He stated that the tool has already shown higher accuracy during tests at RBFT than current clinical criteria and clinicians' assessments.

The project aims to develop a full software prototype through collaboration between AI experts, secondary care specialists, GPs, industry stakeholders, patients, and the public.

This interdisciplinary approach seeks to ensure the RMD-Health system can be effectively integrated into the NHS.