Bangladesh's ACA2 Eye Care Recognized by Moorfields Hospital for Advancing AI with RETFound
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Cure to blindness knows no borders nor our vision
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Total Guests Served
0
Total Fundus image processed
0+
Total Cataract Operated
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Total Major Disease Detected
Our Mission
Amar Chokh Amar Alo (ACA2) is a community-led, AI-assisted network of low-cost eye clinics built with Data Yakka’s digital ophthalmology technology.
These clinics bring sight-saving care to some of the most remote coastal communities in Bangladesh, places with no doctors, no clinics, and, in some cases, no electricity.
In ACA2 clinics, every person is seen with care and dignity. From the moment they arrive, they receive health check-ups, vision tests, and, when needed, advanced retinal imaging.
AI analyses the images instantly. Urgent cases are reviewed in real time by specialists thousands of miles away.
Every step is recorded in a paperless, web-based platform that manages patient flow, follow-ups, and referrals from islands to regional tertiary hospitals.
Hasib Rahman
VP, Data and Artificial Intelligence
Who We Are
We’re a small team of AI engineers, clinical innovators, and community-mobilisation architects.
We build practical, clinically robust, low-cost, AI-enabled eye-care platforms for remote and isolated regions with zero infrastructure.
We work closely with Stanford University’s Dr. Randall Stafford and Dr. Robert Chang, along with Prof. Pearse Keane of Moorfields Eye Hospital and UCL, globally recognised pioneers in public health, digital ophthalmology, and AI-driven eye-disease diagnosis.
Dr. Randall S. Stafford, MD, PhD
Professor of Medicine, Stanford School of Medicine
Ongoing Campaigns
See our ongoing campaigns and join us on the event
Types of Blindness We Cure
At ACA2, we focus on curing and treating a wide range of vision impairments, ensuring that individuals regain their sight and quality of life.
Our Impacts Are Global
Through our initiatives, Stop Blindness has restored sight to thousands of individuals across remote and coastal communities.
Total Patients Served
51103
Percentage of Male Patients
41.38%
Percentage of Female Patients