This is an extract from “AI in health care“, a report by MIT Technology Review Insights.
Many Asian governments have long histories of developing industrial and social incentives to focus business investment and academic output on public policy issues. Singapore in particular has trained a portion of the country’s collective energy and research in AI towards specific health outcomes.
The “Three Highs” are expected to affect 1.5 million Singaporeans—over 26% of the population—by 2020.
In June 2018, AI Singapore, a promotional agency of the country’s National Research Foundation, launched its “AI in Health Grand Challenge,” inviting local academic institutions and businesses to participate in a contest to build AI applications that could contribute to the country’s overall goal of reducing by 20% the number of patients with hyperglycemia, hyperlipidemia, and hypertension by 2024. These three diseases, collectively named the “Three Highs,” are expected to affect 1.5 million Singaporeans—over 26% of the population—by 2020, according to the Ministry of Health.
In March 2019, AI Singapore awarded grants of S$ 5m (US$ 3.6m) each to three finalist project teams, and will invest up to S$ 20m (US$ 14.4m) in one single finalist at the end of two years. One of the finalist teams, dubbed JarvisDHL, is a National University of Singapore (NUS)-led initiative with plans to develop an AI platform, accessible by patients and health-care providers, that will allow them to monitor and evaluate health indicators linked to diabetes, high blood pressure, and cholesterol. A second initiative, also led by a NUS team together with Singapore’s National University Health System, is aimed at developing planning and decision-support algorithms which extend the capacity of Singapore’s Community Healthcare polyclinics, including FoodLg, which monitors patient nutrient intake and provides analysis and patient coaching. A third initiative looks at developing an assessment and intervention platform to assist “Three High” patient management from initial detection to treatment management.