  Artificial Intelligence (AI) is necessary to address the large and growing
deficit in retina and healthcare access globally. And mobile AI diagnostic
platforms running in the Cloud may effectively and efficiently distribute such
AI capability. Here we sought to evaluate the feasibility of Cloud-based mobile
artificial intelligence for detection of retinal disease. And to evaluate the
accuracy of a particular such system for detection of subretinal fluid (SRF)
and macula edema (ME) on OCT scans. A multicenter retrospective image analysis
was conducted in which board-certified ophthalmologists with fellowship
training in retina evaluated OCT images of the macula. They noted the presence
or absence of ME or SRF, then compared their assessment to that obtained from
Fluid Intelligence, a mobile AI app that detects SRF and ME on OCT scans.
Investigators consecutively selected retinal OCTs, while making effort to
balance the number of scans with retinal fluid and scans without. Exclusion
criteria included poor scan quality, ambiguous features, macula holes,
retinoschisis, and dense epiretinal membranes. Accuracy in the form of
sensitivity and specificity of the AI mobile App was determined by comparing
its assessments to those of the retina specialists. At the time of this
submission, five centers have completed their initial studies. This consists of
a total of 283 OCT scans of which 155 had either ME or SRF ("wet") and 128 did
not ("dry"). The sensitivity ranged from 82.5% to 97% with a weighted average
of 89.3%. The specificity ranged from 52% to 100% with a weighted average of
81.23%. CONCLUSION: Cloud-based Mobile AI technology is feasible for the
detection retinal disease. In particular, Fluid Intelligence (alpha version),
is sufficiently accurate as a screening tool for SRF and ME, especially in
underserved areas. Further studies and technology development is needed.
