10151437DCODE - Digital Classification of Observations of Digital ElectrocardiogramsClosedGrant for R&DInnovate UKDCODE is an Ai Consumer Health project looking to develop a Large Language Model (LLM) that will enable to automatic explanation of Electrocardiograms for the consumer. We're pleased to be building DCODE in the Coventry and West Midlands area as we have excellent support in the creative sector and great outreach to the local healthcare services. In 2024, over 428,000 people were on NHS waiting lists for cardiac care in England and Northern Ireland, reflecting significant demand for cardiology services and challenges in meeting growing patient needs. Consumers often struggle to understand electrocardiograms (ECGs) because they are complex medical tests that produce detailed graphs of the heart's electrical activity. The technical nature of the results, filled with intricate waveforms and medical jargon, can be confusing for those without a medical background. This lack of understanding can impact consumers by causing unnecessary anxiety or misinterpretation of their heart health status. It may also hinder effective communication with healthcare providers, leading to misinformed decisions about treatment options or adherence to medical advice. The inability to comprehend ECG results can prevent individuals from recognizing early signs of heart issues, potentially delaying crucial interventions. Ultimately, this gap in understanding can negatively affect a person's ability to manage their cardiovascular health effectively. Understanding ECG is a complex art and explaining it to a consumer in a manner they may understand is complex. By using a Large Language Model and understanding the sequence and impact of specific ECG terminology the project seeks to develop a solution that can machine read in the outputs report of a single lead Holter style ECG and communicate the results to the consumer using AI derived avatars. We will provide the output of DCODE to our customers through our Direct-to-Consumer offering. Using a human Ai avatar to read the results of the Holter ECG to the consumer, providing them with a highly realistic human presentation and explanation of their data, is a novel and creative solution blending creative services, Ai and augmented reality. Humanoid AI avatars offer a powerful way to explain medical conditions by combining advanced technology with human-like interaction. Avatars simplify complex information using natural language and empathetic communication, enhancing understanding and trust. The output is a demonstrator that can then be trialled with local clinicians to ensure that the output is correct and does not contain errors or interpretations that may alarm through false positive or false negative.