Singapore’s largest AI showcase and conference in healthcare solutions organized by NUHS, NUS, and MIT. Featuring prototypes using machine learning algorithms to improve patient outcomes and drive productivity.
The 2nd Healthcare AI Datathon and Expo 2019, co-organised by the National University of Singapore (NUS), National University Health System (NUHS) and Massachusetts Institute of Technology (MIT) Critical Data, was held form the 18th to 21st of July 2019. Drawing more than 700 doctors, data scientists, data engineers, software engineers, and innovators in healthcare to showcase prototype solutions using AI, predictive analytics, and machine learning algorithms. The event was graced by Ms Chan Lai Fung, Permanent Secretary of National Research and Development and Chairman of Agency for Science, Technology and Research.
A total amount of S$6.4 million in various grants and seed funds are being invested by NUHS in the next two to four years on AI-powered initiatives, using machine learning algorithm, imaging, computer vision, precision medicine, and predictive analytics. Many of these projects are now at stages of clinical trials, validation, and commercialisation, with promise to drive impact in patient outcomes and productivity. The concepts and prototypes were showcased at this expo.
Driving AI for the greatest impact from hospital to community and letting more access AI-enabled healthcare services in the comfort of their home, will be our goal for the next few years,” said Assistant Professor Dr Ngiam Kee Yuan, NUHS’s Group Chief Technology Officer, whose NUHS Research Office organized the most established and large scale conference and exhibition focusing on AI in healthcare in Singapore for its second year.
The conference, exhibition, workshops, and seminars were held at The Star Gallery, The Star Performing Arts with a separate site at NUS hosting workshops on AI in healthcare. This was followed by a two-day data-centric, Datathon where 20 cross-disciplinary teams collaborate to come up with innovative solutions using healthcare analytics to address healthcare issues. [APBN]