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Predictive AI Can Be the Prescription for Future of Singapore's Healthcare
The Straits Times
|August 07, 2025
The real transformation is not about replacing doctors with AI, but about empowering them with it.
Singapore's Health Minister Ong Ye Kung's announcement in June 2025 that the country will integrate predictive artificial intelligence (AI) into its national Healthier SG marks a significant turning point.
Leveraging health records and AI to forecast disease risk years in advance will allow the industry to chart a course for a more proactive, preventive and personalized era of medicine.
Yet, this news might spark unease, especially around AI outperforming humans in the medical field, from simple administrative tasks to complex diagnostic responsibilities such as treating diseases or even mapping tumors.
It is easy to imagine a future where the physician's nuanced judgment is replaced by the logic of an algorithm. However, this vision is misguided. The real transformation is not about replacing doctors with AI, but about empowering them with it.
The central challenge of our time is not adapting to a world run by AI, but in preparing the next generation of clinicians to wield these powerful new tools.
THE DIAGNOSTIC CO-PILOT
A modern-day clinician faces a deluge of data on a daily basis.
For example, a radiologist might review dozens of complex scans every hour, where fatigue can potentially lead to errors.
Now, imagine an AI co-pilot trained on millions of images.
As demonstrated in a recent study from Northwestern Medicine, such a tool can match the accuracy of doctors in outlining lung tumors on CT scans, and can also flag high-risk areas that are sometimes missed.
When data analysis is powered by AI, the radiologist can focus on the most complex aspects of the case, consult with colleagues, and, most importantly, communicate with the patient. The technology cuts through vast datasets by providing unbiased second opinions that reduce diagnostic errors and standardize care quality. This augmentation is critical in pattern recognition and, by extension, the delivery of care.
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