DeepSarco: 3D AI 사르코페니아 진단

Sarcopenia (muscle loss due to aging) is a cause of health problems in the elderly, such as falls and metabolic diseases, but diagnosis requires expensive imaging equipment such as CT/MRI, so screening is not well performed.

As a result, many elderly people are diagnosed with sarcopenia too late after it has progressed, missing the golden time for treatment. Existing simple muscle strength tests (such as grip strength measurement) are inaccurate and have limitations as early diagnostic tools.

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DeepSarco uses AI to predict muscle mass and determine the presence of sarcopenia based solely on a photograph of the patient's entire body or a specific area taken with a 3D depth sensor [76].

The patient simply stands in the hospital, and the AI calculates the muscle ratio in the body composition based on 3D scan data and automatically reports the risk of sarcopenia by comparing it with existing diagnostic criteria. This process is safe and convenient because there is no radiation exposure or blood test, and it can be performed even in remote medical situations [77].

In addition, the AI generates customized reports considering the patient's gender, age, etc., so healthcare providers can refer to it for exercise/nutrition prescriptions for each patient.

In the end, the key innovation is that sarcopenia can be screened early, quickly, and easily without expensive equipment.

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Medical institutions such as hospitals and checkup centers (B2B) are the main customers.

Departments of orthopedics, rehabilitation medicine, and family medicine can introduce it as a sarcopenia screening package, or comprehensive examination centers can add it to the examination items for the elderly. In addition, nursing facilities and healthcare startups can license and provide services.

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As the demand for sarcopenia management is rapidly increasing due to the aging of the world's population, the market preemption effect is expected as it is currently difficult to find similar solutions.

After domestic approval, global expansion such as FDA and CE certification is also possible in the future. Furthermore, it is conceivable to lighten this technology into a home app/device so that seniors can check themselves at home.

However, as it is a medical AI, it may take time to accumulate clinical evidence and acceptance in the medical community.

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It became known internationally by winning the CES Innovation Award (Digital Health category).

Experts see high potential, saying that "the era of diagnosing muscles with just a mobile phone camera" has arrived, but at the same time, they agree that "securing trust in the medical field is key."

It is the opinion that excessive expectations are dangerous because clinical trial data is not yet sufficient and market verification is insufficient. It is innovative based on the CES showcase, but it is a realistic assessment that there is still a long way to go before it is recognized as a standard in the medical community.

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