artificial intelligence and distributed telemedicine for computer-aided diagnosis of diabetic retinopathy

explore us

About Us

Earlier Diagnostics

Trained technicians take fundus pictures from patients anywhere, without ophthalmologists in place. retinar AI software automatically detects signs of vision threatening diabetic retinopathy to communicate the diagnosis to the patient.

Better Reports

Referrable cases are automatically sent to certified experts to be further revised and to confirm the diagnosis. retinar AI tool aids these clinicians to carefully examine each picture they get, yielding more accurate reports in less time.

Faster Treatment

Patients with referrable cases confirmed by the experts are automatically assisted by retinar, getting recommendations about the closest clinics and medical centers that can treat their pathology.

Preventing Blindness

Diabetic Retinopathy: the leading cause of blindness in working age adults

Diabetic mellitus is a pandemic that affects around 8.5% of the world’s adult populations. Every person with diabetes is at risk of developing diabetic retinopathy (DR). Approximately 1 in 3 people with diabetes have some degree of DR, and 1 in 10 will develop a vision threatening form of the disease.

  • 415 million people in the world suffer from diabetes

  • 145 million in the world have some form of DR

  • 10 million have vision threatening DR

  • 30% of people with diabetes get its eye exam

  • 3.7 ophthalmologists per million population in low income countries

Artificial intelligence to prevent blindness

Our team of data scientists develops cutting edge AI tools that aid clinicians to diagnose eye diseases.

Contact Us!

Our Services

Automated DR Screening

Any primary care unit, optometrist or diabetologist can use retinar to automatically detect referrable diabetic retinopathy cases using our AI tool.

A Platform for Remote Reading

Certified retina experts can read images remotely and on-demand using our platform, allowing them to reach more patients without moving from their place.

Computer-assisted Diagnosis

Our AI technology aids ophthalmologists to increase their throughput analyzing fundus pictures, bringing efficiency to the reading process.

AI Assisted Fundus Image Acquisition

With a minimum training, any technician can use our AI support to get high quality fundus pictures, reducing costs and ensuring better diagnostics.

Networks for Treatment

Any clinic and/or treatment specialist can register in our platform to be recommended by retinar to patients in need.

Logistic Solutions to Patients

Patients no longer need to search clinics for treatment by themselves. retinar recommends the closest health centers to start the treatment right away.

The right diagnosis. Everywhere. Anytime.

retinar aids patients around the world to access to accurate diagnostics regardless of the regional availability of ophthalmologists.

Fundus image based

Our platform is entirely based on fundus photographs, a non-invasive & cost-effective medical imaging technique that can be easily captured by trained technicians.

AI based instant referral

Our AI can determine in-place and with high accuracy if the patient needs referral to an ophthalmologist. In that case, the image is transferred to be analyzed by retina experts.

Connecting professionals

retinar allows any certified expert in retina to join as a reader. Using AI, we aid them to produce better reports and to connect rapidly with patients that need treatment.

Treatment recommendations

We provide patients at risk with recommendations of hospitals and clinics close to their living places, reducing logistics costs & bringing rapid treatment to prevent blindness.

Our Team

José Ignacio Orlando, PhD

José Ignacio Orlando, PhD

Co-founder / AI staff

Assistant Research @ CONICET (PLADEMA / UNICEN). retinar project leader and AI specialist.

Mercedes Leguía, MD

Mercedes Leguía, MD

Co-founder / Clinical staff

Ophthalmologist. Director of the Ophthalmology Department @ Hospital Alta Complejidad El Cruce (Florencio Varela).

Ignacio Larrabide, PhD

Ignacio Larrabide, PhD

Co-founder / Medical imaging staff

Independent Research @ CONICET (PLADEMA / UNICEN). Expert in medical image analysis.

Tomás Castilla, Eng.

Tomás Castilla, Eng.

AI staff

Software Engineer. AI developer.

Marcela Martínez, MD

Marcela Martínez, MD

Clinical staff

Ophthalmologist. Director of Martinez Ophthalmological Center (Pehuajó).

Alejandro Koch, MD

Alejandro Koch, MD

Co-founder / Clinical staff

Cardiologist. Cardiology Service @ Hospital Alta Complejidad El Cruce (Florencio Varela).

Contact Us

Contact Details

retinar is an ungoing project and we’re very excited to make it happen! If you want to know more or you want to join our multidisciplinary team of clinicians and computer scientists, feel free to contact us!

PLADEMA, Campus Universitario UNICEN, Tandil, BA, Argentina
Phone: +54-249-438-5690 (Int. 2411)
Fax: +54-249-438-5690

Latest News

Funding from Agencia I+D+i (Argentina) for retinar

We received funding through the 2021 call for PICT start-ups from Agencia Nacional para la Promoción de la Investigación, el Desarrollo Científico y la Innovación (Agencia I+D+i) to fund our research in retinar, under the supervision of Dr.

Read more

retinar was awarded by NVIDIA Corporation

retinar was selected as member of the NVIDIA Applied Research Accelerator Program. Our project, entitled “retinar: assisting remote diabetic retinopathy screening with AI tools”, our joint initiative between UNICEN and Hospital El Cruce was awarded with 500 hours on V100 GPU instances via SaturnCloud.

Read more
View All Posts