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ARTIFICIAL INTELLIGENCE FOR BETTER HEALTH AI is shaking up the world and nowhere more so than in healthcare. Vast amounts of genetic and other data can now be computed to quickly identify biomarkers and new pathogens and provide more precise and personalised treatments. However, realising this potential is not a simple matter of pushing some buttons or typing some keys. A lot of groundwork still needs to be done to collect and analyse the data and understand its implications. The Laboratory of Data Discovery for Health (D 2 4H) will be at the forefront of this work. The Laboratory will apply data-driven approaches and AI analytics in areas that are of global concern and reflect HKU’s expertise, including tracking emerging pathogens and investigating the threats and responses to these and other pathogens, particularly respiratory viruses. The aim will be to deepen understanding and develop new pathways to treatment. D 2 4H is led by Professor Gabriel Leung, Dean of Medicine, who regularly advises national and international bodies such as the World Health Organization (WHO), World Bank and Chinese Center for Disease Control and Prevention. Other members come from HKU, Harvard University, the London School of Hygiene and Tropical Medicine, University College London and the University of Sydney. “We are very excited by the rapid advances in AI and the high hopes that it will be an instrumental and transformative catalyst for realising precision medicine and global health democratisation,” he said. In terms of global health, the Laboratory’s members plan to develop a platform that combines all the metagenomic data in the world into a single integrated databank to detect emerging pathogens. They will also try to determine the pathogens behind human respiratory infections where the cause has been unknown – a persistent worry which has taken centre stage with the COVID-19 pandemic. Laboratory scholars will also develop new methods for predicting seasonal influenza epidemics, sequence the genomes of bacteria to help determine drug resistance, and improve surveillance and diagnosis of respiratory infections. Preventive measures are also high on the agenda and one of the Laboratory’s centres will focus on “vaccine hesitancy” – people’s resistance or reluctance to vaccinate – using digital influencer platforms. The WHO has named vaccine hesitancy one of the top ten threats to global health. This centre will also seek to identify antibodies to high-threat pathogens and optimise breast cancer screening so it is less invasive and more personalised. Two final areas of interest will be to develop new treatments for non-communicable diseases, using data from Hong Kong’s Hospital Authority, and to improve the application and speed of “omic” data, which is key to personalised medicine. Together, the full range of the Laboratory’s projects are expected to result in new treatments, start-ups and knowledge that will help to drive the future of medicine. We are very excited by the rapid advances in AI and the high hopes that it will be an instrumental and transformative catalyst for realising precision medicine and global health democratisation. 16 Feature