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How AI in healthcare can improve patient outcomes

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Artificial intelligence offers solutions to cost and quality concerns in healthcare

Spotting and preventing medical problems early on is far cheaper and more efficient than catching them late.

The problem for overworked physicians is that issues are not always easy for human eyes to detect.

Artificial intelligence in healthcare is helping to fill in the gaps by diligently mining as much data as possible and making helpful suggestions that can lead to potential medical problems being identified earlier.


Globally, the healthcare sector is experiencing staff shortages as well as pressure on costs. In South-east Asia, cost and quality are the two key concerns for the health care providers.

According to Dr Loke Wai Chiong, Deloitte Southeast Asia's Health Care Sector Leader, medical costs are increasing due to demographic change and the rise in chronic disease population.

He added: "Governments are starting to evaluate the true cost effectiveness of medical treatments. They are also looking for innovative ways to deliver quality patient-centred care by leveraging digital technologies to reduce costs while improving outcomes."

Singapore is no exception. Healthcare expenditure in the country is projected to go up to US$12 billion (S$16.4 billion) in 2020 from US$9 billion in 2015.

One of the most promising approaches to the global healthcare challenge is the application of technology.

A key element of this approach is artificial intelligence. The processes of healthcare generate huge quantities of data that, when correctly analysed, can help treat patients faster and more effectively, and also avoid errors.

AI does this by processing vast amounts of historical data using statistical models that identify patterns. It can then process new data against the historical model to look for similarities that may not be immediately evident to a physician.


Around the world, AI solutions are being developed to help with everything from oncological scan analyses to the predictive capability of alerting nurses to a patient's risk of falling.

In Singapore, the leader in South-east Asia for digital healthcare, several AI projects are underway in the national healthcare system.

For example, Aunty Sal is a chatbot that helps users filter information related to aged care.

Through the app, all aged-care related services can be accessed on one platform. The app is also linked to government social services, so caregivers can access information on available financial assistance.

Another state-of-the-art AI technology that could soon make its way into local hospitals is a contactless vital signs monitor, which reads a patient's heart rate and blood pressure remotely. This device will save nurses time when making their rounds. It can even monitor a patient during his sleep, without the need to wake him.


The existence of huge volumes of historical and real-time data holds out the promise of more accurate AI models and better preventative care. The challenge for hospitals lies in processing that data, which is often delivered in high volume thanks to high-resolution medical imaging, and deriving meaningful insights from it.

The writer is the vice -president and general manager of Hortonworks Asia Pacific