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​AI.SG Grand Challenge for preventing diabetes, hypertension and hyperlipidemia. For this, Health Services Research Centre (HSRC) is collaborating with National University of Singapore  (NUS) to develop an AI system called JARVISDHL

The project aims to integrate multiple solutions into a consolidated AI platform which can be used to help primary care teams stop or slow disease progression and complication development in DHL patients by 20% in 5 years.

We aim for the following transformations:

• From reactive care to predictive care: The current sequential referral system is non-ideal as it is reactive and tends to play catch-up disease progression, while greater impact could have been achieved if interventions were commenced earlier in the disease spectrum. The advent of AI and machine-learning can enable accurate predictive stratification of at-risk individuals, so that it is possible for preventive actions to be taken well before the onset of symptoms.

• From "one-size-fits-all" to personalised care: Greater impact could be achieved if healthcare can be customized on a per individual basis based on local contexts. The abundance of electronic medical records from the local populations, together with new health data sources (for e.g., lifelogs) of the individuals, can be harvested with sophisticated learning algorithms to recommend locally and individually-tailored treatment options for our patients.

• From passive patient to activated patient: The DHL patient's role in his or her own healthcare tends to be passive – in a typical visit to the clinic, the doctor dictates the decisions and the patient follows. Greater impact could have been achieved if the patient were empowered to take an active role in his or her own care.

Ultimately, the platform can be scaled up to provide personalised and predictive care for the population with other chronic diseases in other regional health systems, throughout the healthcare system in Singapore, as well as globally.


From left: Dr Janil Puthucheary, Prof Tan Ngiap Chuan, Prof Lee Mong Li, Prof Ng See Kiong, Prof Wynne Hsu, Prof Marcus Ong Eng Hock, Prof Wong Tien Yin