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Data Analytics for Long-Term Conditions – TechToday

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The use of AI in health is showing great promise, particularly in addressing the rise of chronic diseases. A session at the Digital Health AI and Data event will focus on how AI can help patients with multiple long-term conditions (MLTC). Researchers from four UK research groups, including Simon Fraser from the University of Southampton, will discuss how AI and data analytics can be used to study England’s 14 million people with MLTCs. Fraser emphasizes the importance of understanding the development of chronic conditions across a person’s lifetime and believes that AI methods can assist in analyzing data from birth cohorts and healthcare records.

The challenge lies in linking different types of data sets, as birth cohorts provide rich social data but limited information on long-term conditions, while routine healthcare data is rich in long-term condition data but limited in social information. Fraser foresees the need for new methods to analyze and integrate these data sets securely and reliably. Ultimately, the goal is to identify opportunities for preventing or delaying the onset of long-term conditions. This session at the AI and Data event aims to explore the potential of AI in addressing the challenges faced by patients with MLTCs and finding innovative solutions through data analysis.

Digital Health AI and Data, organized by the creators of Digital Health Rewired and Digital Health Summer Schools, offers a diverse program covering AI, analytics, data, and research. The event is CPD accredited and open to various sectors, including the NHS, public sector, start-ups, charities, education, and research. While the session featuring Simon Fraser and other experts is free for eligible attendees, commercial tickets are also available for purchase. The event aims to foster collaboration and knowledge-sharing in exploring the possibilities of AI and data in healthcare.

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