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Industrial Technology Research Institute

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Portable Edge AI-DR

Technology Overview

Figure 1. Portable Edge AI-DR
Figure 1. Portable Edge AI-DR

This technology is a collaboration of the minds of the human brain and artificial intelligence through the expertise of ophthalmologists and AI analysis. Composed with complementary AI models, it can perform individual diagnostic tasks like doctors, such as categorizing and detecting, and improve the efficacy of overall interpretation. The combination of hardware and software into a portable medical device makes it easy to carry around and can shorten the time to diagnosis. The technology, therefore, increases the early detection rate of diabetic retinopathy (DR) for potential patients and reduces the cost of healthcare and social care.

  • Leading AI-assisted Diagnosis System
    • Currently the only AI detection technology in the world that can detect the four main lesions (Microaneurysms, Hemorrhages, Soft Exudates, Hard Exudates) in DR, label the corresponding locations clearly, and assist doctors in interpreting the severity of the condition. (Figure 2)
    • In addition to diagnosis, with the ability to filter poor-quality images caused by dirt, shadows, and eyelashes, this technology can remind doctors or technicians to retake the image and accordingly prevent misinterpretation by artificial intelligence.
  • Portable Solution & SaMD Clearance
    • The world’s first AI-DR handheld fundus camera, which has been cleared by the TFDA as a Class II medical device providing both CADx and CADe, was launched in Taiwan in July 2021. (Figure 1)

Through intensification of the AI solution, this technology has extended the capability to simultaneously detect both diabetic retinopathy and diabetic macular edema (DME) and currently focuses on other 10+ ocular fundus abnormalities common to the general public.

Applications & Benefits

Portable Edge AI-DR uses AI to assist non-ophthalmologists in their diagnoses and solve the problem of uneven distribution and lack of ophthalmologists. By identifying DR stages and lesions, this innovation improves diabetes health monitoring and management and helps lower the risks of vision loss or blindness caused by DR.

  • Innovative Diabetes Care Scenario
    • By helping non-ophthalmologists comprehensively conduct the detection of subtle lesions in fundus images, this innovation eliminates the inconvenience of referrals to ophthalmologists for patients without more than mild DR (mtmDR). (Figure 3)
    • Physicians can effectively grasp the patient's diabetes development status by tracking the changes in fundus symptoms over time. This is crucial to diabetes management as the changes in the fundus symptoms reflect better than blood sugar levels tested, which patients can control right before hospital revisits.
    • Beneficial for non-ophthalmologists and optometrists to provide advanced care for diabetic eye complications, this competitive AI-aided system and evolutionary service scenario will create new market opportunities for the global healthcare industry.
  • Social Responsibility and Impact
    • Applicable for both community and hospital settings, the mobile service provided by Portable Edge AI-DR effectively assists in DR screening and early intervention and thus greatly reduces medical costs.
    • In collaboration with local clinics, Lions clubs, and medical centers, the system has been used for eye examinations for over 47,000 diabetics in Taiwan and successfully promoted a significant increase in DR screening rate in counties, e.g. a 27% increase in Taitung. (Figures 4 & 5)
Figure 2. AI Decision Support Technology of Fundus Image in Diabetes Mellitus
Figure 2. AI Decision Support Technology of Fundus Image in Diabetes Mellitus

Figure 3. Innovative Diabetes Care Scenario with Non-Ophthalmologists
Figure 3. Innovative Diabetes Care Scenario with Non-Ophthalmologists

Figure 4. Regular Eye Examinations in Clinics of Diabetes Shared Care Network
Figure 4. Regular Eye Examinations in Clinics of Diabetes Shared Care Network

Figure 5. Early Screening of DR in Remote Areas by Medical Centers
Figure 5. Early Screening of DR in Remote Areas by Medical Centers

Figure 6. Innovation Awards Recognition
Figure 6. Innovation Awards Recognition



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