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Singapore AI heart scan tool heads for wider hospital testing

Source: Healthcare Asia

Singapore researchers are moving an AI-powered heart scanning tool from the lab to the clinic, with plans to expand testing across multiple hospitals before seeking regulatory approval to measure heart damage from MRI scans.

Singapore AI heart scan tool heads for wider hospital testing
SGAI Daily

Singapore researchers are moving an AI-powered heart scanning tool from the lab to the clinic, with plans to expand testing across multiple hospitals before seeking regulatory approval. The tool uses artificial intelligence to measure heart damage from MRI scans, a task that traditionally requires specialist interpretation and takes considerable time.

The AI system analyses cardiac MRI images to quantify damage, potentially enabling faster and more consistent assessments than manual review. Heart disease remains one of the leading causes of death in Singapore, and the tool aims to support cardiologists by providing objective measurements that can guide treatment decisions.

Wider hospital testing is the critical next step before the tool can be submitted to the Health Sciences Authority for regulatory clearance. If validated across diverse patient populations and clinical settings, the technology could become part of routine cardiac care in Singapore's public hospitals.

Singapore's healthcare AI ecosystem has grown rapidly, with the Ministry of Health actively supporting clinical AI validation studies. The National Heart Centre and university-affiliated hospitals have been early adopters of AI-assisted diagnostics, and this tool represents the kind of homegrown healthtech that the government has been encouraging through grants and regulatory sandboxes.

Why it matters for Singapore: A clinically validated AI heart tool developed locally would strengthen Singapore's position as a medical AI hub in Asia. It also addresses a real gap: Singapore's ageing population will drive demand for cardiac screening, and AI-assisted diagnostics could help the healthcare system scale without proportionally increasing specialist workload.