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Airdoc is committed to the early screening and predictive analysis of chronic diseases and owns the world's largest retinal image database

AI-FD16H is a fully automatic mydriasis-free fundus camera specially designed and developed for artificial intelligence fundus image analysis. It is non-invasive and suitable for rapid screening, with automatic pupil tracking, positioning, focusing and shooting. The AI seamlessly connects to capture images and conducts real-time analysis. It has high-definition imaging of 12 million pixels and a large field of view of 50°. The nine-point internal fixation covers a wider field of vision. It has a built-in screen for real-time shooting preview, checking image quality and user management.
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AI-FD16H is a fully automatic mydriasis-free fundus camera specially designed and developed for artificial intelligence fundus image analysis. It is non-invasive and suitable for rapid screening, with automatic pupil tracking, positioning, focusing and shooting. The AI seamlessly connects to capture images and conducts real-time analysis. It has high-definition imaging of 12 million pixels and a large field of view of 50°. The nine-point internal fixation covers a wider field of vision. It has a built-in screen for real-time shooting preview, checking image quality and user management.

Airdoc can obtain a "one-time 44 chronic disease assessment report" in as fast as three minutes, including 9 chronic disease risks and 35 common retinal abnormalities. Literature in The Lancet points out that Airdoc's AI computing power is comparable to that of ophthalmologists. It is used in hospitals, physical examination centers, optical centers for glasses, schools, families, pharmacies, airports and other scenarios, and is suitable for people of different races and ages. Welcome to Booth 11A04-3 until 14th November or www.airdoc.com .

 

 

View original content: https://www.prnewswire.com/news-releases/airdoc-is-committed-to-the-early-screening-and-predictive-analysis-of-chronic-diseases-and-owns-the-worlds-largest-retinal-image-database-302301291.html

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