AI in Health Summit

Must-see talks

Are you heading to the new AI in Health Summit? Here are five recommended sessions from this year’s agenda:

1. Where can AI make the biggest impacts in healthcare? | 9.05am
   Natasha Loder, Health editor at The Economist, moderates this session with Lawrence Tallon, Chief Executive at Medicines and Healthcare products Regulatory Agency (MHRA), and Alastair Denniston, Executive director, CERSI-AI and professor of regulatory science and innovation, University of Birmingham. The fireside chat will examine how AI can benefit clinical and administrative efficiency, as well as how its potential can be realised across health and care.
   
2. Reducing the burden on health systems | 9:20am
   Health systems across the world are facing critical challenges, including ageing populations, chronic disease and budget restrictions. Representatives from King’s Fund; Ministry of Health, France; African Neonatal Network and Vitality examine how AI solutions, including generative AI and AI symptom-trackers, can help to ease the burden.
   
3. Data, privacy, bias | 4:30pm
   Nicola Byrne, the UK’s National Data Guardian for health and social care, delivers a speech on the three core concerns associated with the deployment of AI: data flowing between systems; pateints’ privacy; mitigating biases within AI models.
   
   
4. Global regulations for trust and transparency | 4:40pm
   A clear, unified approach to regulating AI is a crucial step – but how do we get there? This panel with Hardian Health; University of Sydney; Scarlet; and World Health Organisation will debate ideas on how proper safeguarding can be implementing, whilst also allowing for agile procurement of AI solutions.
   
5. Breaking down the barriers to healthcare innovation | 5:25pm
   Cost, privacy and ethical concerns are just some of the challenges around implementing AI systems for healthcare, but how can these concerns be eased? In one of the final sessions of the day, hear insights from World Health Organisation (WHO), Coalition for Health AI (CHAI) and ustwo on ways to increase clinical and consumer acceptance.