Big data is gaining traction in reshaping the future of healthcare landscape globally. Here, we study how data science methodologies can be deployed in remodeling the local healthcare landscape through multi-disciplinary collaboration with clinicians and scientists across the SingHealth community.

Diabetes J.A.R.V.I.S – A Vision for Using Artificial Intelligence (AI) to Revolutionise Diabetes Care
Diabetes poses a major healthcare problem globally and locally. Complications brought about by the medical condition such as diabetic retinopathy, diabetic nephropathy, diabetic foot ulcers will be discussed by the various area experts and how AI plays a role in diabetes management in Singapore to improve care for patients, reduce cost for healthcare systems, and facilitate practice of personalized medicine by healthcare professionals.

SMARTCare – Building the Healthcare Systems of the Future
SMARTCare aims to create an AI-enabled SMART Learning Healthcare system that is able to manage resources and deliver optimal, cost-effective care with improved outcomes and experience-of-care for a rapidly ageing population. Using SingHealth as a test-bed, SMARTCare aims to develop AI-enabled systems to address the various issues; intelligent command centre, chatbot, triage, semi-automated ICUs, medication vending machine, Operating Theatre scheduling, perioperative monitoring, value-driven outcomes, Hip Fracture Bundled Care Pathway amongst others.

Real-time Flagging of PRISM Participants in the SingHealth Clinical Environment via eHIntS
SingHEART / Biobank is a longitudinal cohort of consented, normal volunteers that have been comprehensively genotyped (whole-genome sequencing) and phenotyped (cardiac MRI, lifestyle questionnaire, activity tracking, lipidomics). Currently being tracked periodically using yearly phone calls, the infrequent nature of these follow-ups and the reliance on volunteer recollection may result in an inaccurate picture of their health status. Together with HSRC and IHiS, PRISM seeks to overcome such limitations by interfacing with the SingHealth EMR system via eHIntS and enable near real-time and accurate updates on their health status through data science.