AI analyses heart patterns, identifies conditions, and issues reports in a few minutes, increasing efficiency



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Left to right: Synapxe CEO Ngiam Siew Ying, Synapxe Director of Innovation Capabilities Enablement Glenn Neo, A*STAR Prof Tan Sze Wee, A*STAR CEO Frederick Chew

A locally developed system that uses artificial intelligence to analyse heart scan images can identify conditions in just a few minutes and generate a report within seconds. This is of great help to radiologists who have to analyse hundreds of scanned images every day and can increase work efficiency by up to 20 times.

The new system, APOLLO, was co-developed by the Agency for Science, Technology and Research (A*STAR) in Singapore and multiple local medical and research institutions. Based on 3 million computed tomography (CT) scans of 5,000 local patients, the system trains artificial intelligence to identify various symptoms of heart disease, including cardiac calcification, excess fat tissue, and plaque.

These conditions can be traced on CT scan images. Still, the radiologists responsible for analysis have to look at hundreds of images every day, which is a heavy workload and may miss some symptoms. According to clinical trials, with APOLLO, the rate of missed or delayed diagnoses can be reduced by up to 37%.

The new system analyses CT scan images, saving up to 90% of the time.

In addition, the new system can significantly shorten the analysis time of each CT scan, saving up to 90% of the time, especially for images with complex conditions. Once these CT scan images are uploaded to APOLLO, the system can identify the symptoms within 10 minutes. After verification, the radiologist only needs to click on the computer screen to generate a report within a few seconds.

Like all other medical innovations, developing this system is only the first step. It must be tested and continuously improved based on feedback from radiologists. It can only be widely used by medical institutions once the system stablises.

A*STAR signed a memorandum of understanding with Synapxe on Friday (March 8) to prepare to test APOLLO through the Artificial Intelligence Medical Imaging Diagnostic System (AimSG) platform.

AimSG was launched last year to bring together various local medical imaging artificial intelligence systems. Currently, most of the three major medical clusters are developing and using their systems. AimSG is a nationwide platform. Medical staff from all local public medical institutions can log in to try it out.

Artificial intelligence could ease the manpower crunch for radiologists.

Glenn Neo, Director of Innovation Capabilities Enablement, Synapxe, said that the world is facing a shortage of radiologists, and artificial intelligence can significantly alleviate this problem. However, when it comes to the safety of patients, the diagnostic process must be controlled by professional medical staff, no matter how advanced artificial intelligence is. To ensure that the new system can indeed help radiologists improve their workflow, AimSG places great importance on the collection of user feedback.

Neo said that the medical imaging industry in Singapore leads the world in the application of artificial intelligence. Nevertheless, this industry still has great potential for development. In addition to heart disease, AimSG will bring together artificial intelligence systems for more modalities in the next three years.

Frederick Chew, the Chief Executive of A*STAR, revealed that in addition to medical imaging, A*STAR has also invested heavily in developing new drugs. He is very optimistic about the development prospects of artificial intelligence, believing that artificial intelligence will help direct and progress medical research and development and can make the research and development process "faster, cheaper, and better."

Source: Lianhe Zaobao © Singapore Press Holdings Limited | Reproduced with permission.


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