Artificial intelligence (AI) technology is increasingly being integrated into healthcare services across the NHS, demonstrating promising advancements in the diagnosis and treatment of various medical conditions. From enhancing cancer detection during colonoscopies to improving fracture identification in x-rays and assessing skin lesions for cancer, AI is proving to be a valuable asset in the medical field.
A notable study undertaken by Bolton NHS Foundation Trust has revealed significant improvements in cancer detection rates during colonoscopies. Conducted as part of the COLO-DETECT trial, this research involved over 180 patients between September 2021 and March 2023. The trial was led by South Tyneside and Sunderland NHS Foundation Trust, alongside Newcastle University. Utilising the GI Genius AI device, the trial resulted in an 8.3% increase in adenoma detection, potentially reducing the incidence of post-colonoscopy colorectal cancer by 25% and decreasing fatal cases by 41–42%. This enhancement in detection is considered critical, with the potential to dramatically impact patient outcomes.
In another instance of AI application, East Suffolk and North Essex NHS Foundation Trust has begun employing AI technology to assist in fracture detection. The Boneview technology is set to be implemented at Ipswich Hospital, Colchester Hospital, and the Clacton Urgent Treatment Centre. This AI scans thousands of x-rays for fractures that may escape detection by the human eye. Although all x-rays will continue to be reviewed by clinical staff, AI is expected to expedite the diagnostic process, especially in cases awaiting radiological review.
Meanwhile, the NHS in Suffolk and North Essex has been trialling AI for skin cancer detection. The Skin Analytics DERM system is being extended to Colchester as part of a pilot scheme that will run until March 2025. Since its initial roll-out in Clacton in August 2023, the system has analysed photographs of skin lesions and moles, checking for 11 common malignant, pre-malignant, and benign skin conditions. When the AI identifies a potential cancer, it suggests referrals to consultant dermatologists, ensuring a secondary review before any patient is recommended back to general practitioners for non-cancerous findings. This project aims to manage patient demand more efficiently by reducing unnecessary hospital visits, a sentiment echoed by Dr Alice Parr, cancer lead for the NHS Suffolk and North East Essex Integrated Care Board.
These individual advancements are part of a broader trend within the NHS and beyond, backed by considerable government investment. In June, the Department of Health and Social Care announced a £21 million fund dedicated to AI technologies aimed at speeding up diagnosis for conditions such as cancers, strokes, and heart diseases.
In addition to real-world applications, insights from expert panels suggest that AI's role in healthcare is expanding, not only for diagnostics but also in addressing waiting lists and crafting personalised care plans. Concurrently, the University of Huddersfield is developing a secure platform for sharing threat intelligence to protect AI diagnostic tools from cyber threats.
Further collaboration at Leeds Teaching Hospitals NHS Trust with startup Newton's Tree will see AI platform implementation aiming to enhance the scaling and effectiveness of AI applications across the trust. Also noteworthy is the European AI Act, a framework designed to mitigate risks associated with AI, underscoring the significance of maintaining trustworthy AI systems.
These initiatives collectively underscore the transformative potential of AI in healthcare, highlighting ongoing efforts to incorporate advanced technologies while ensuring safety and reliability. AI's integration promises significant enhancements in medical diagnostics and patient care, driven by collaborative efforts and strategic investments.
Source: Noah Wire Services