Early Diagnosis of Diabetic Retinopathy | Bloomberg vouch report
Bloomberg Published – iHealthScreen Inc. Announces CE Certification for iPredictTM Automated AI System for Early Diagnosis of Diabetic Retinopathy (DR)
iHealthScreen Inc. Announces CE Certification for iPredictTM Automated AI System for Early Diagnosis of Diabetic Retinopathy (DR), Age Related Macular degeneration (AMD), and Glaucoma Suspect
iHealthScreen is the first company in the USA to receive a CE certification
for simultaneous diagnosis of DR, AMD, and glaucoma suspect.
NEW YORK — May 25, 2021
iPredict^TM AI Eye Screening System provides fully automated diabetic
retinopathy (DR), age related macular degeneration (AMD), and glaucoma suspect
screening, including retinal imaging, and immediate reporting of actionable
results. Using the iPredict^TM System, ^ primary care and various specialty
practices can accurately and efficiently screen diabetic patients for DR,
people over 50 for AMD, and those with a family history of glaucoma or other
risk factors for suspected glaucoma.
Once high-resolution images of the patient’s eyes have been captured using a
color fundus camera and submitted to the iPredict^TM AI System, the screening
results are available in a fully automated report in less than 60 seconds. The
entire test can easily and reliably be completed within 5 minutes.
iPredict’s CE certification indications for use as follows:
- iPredict-DR can detect more than mild DR or vision threatening DR such as
severe non-Proliferative DR, proliferative and diabetic macular EDEMA.
- iPredict-AMD can detect referable AMD such as intermediate to late AMD and
non-referable AMD such as early or none.
- iPredict-glaucoma detects glaucoma suspects based on abnormal optic discs.
If referable stage disease is detected for any of these conditions, the
iPredict automated report recommends a visit to an Ophthalmologist for
appropriate treatment. Otherwise, in accordance with standards of care, a
follow up visit in one year is suggested. iPredict is indicated for use by
healthcare providers in clinics, hospitals or other healthcare facilities to
automatically detect DR, AMD and glaucoma suspect.
iPredict achieved very high accuracy in the diagnosis of these diseases with
referable and non-referable status. For disease diagnosis:
- iPredict-DR achieved up to 98.48% accuracy with 97.32% sensitivity and
98.75% specificity for identification of referable DR.
- iPredict-AMD achieved up to 99.2% accuracy with 98.9% sensitivity and
99.5% specificity for identification of referrable AMD.
- iPredict-glaucoma achieved 89.67% accuracy with 83.33% sensitivity and
93.89% specificity for glaucoma suspect.
“This technology could be particularly useful in identifying someone who has
slipped across the boundary to progress into severity,” Dr. Theodore Smith
(Professor in Ophthalmology and Neuroscience at Icahn School of Medicine at
Mount Sinai, New York) said. “By alerting patients and their physicians to the
potential dangers ahead, we believe this screening tool could play a very
important public health role.”
“This is a major milestone for iHealthScreen. iPredict^TM eye disease
diagnostic tools will help prevent blindness for millions of people and save
insurers countless millions of dollars in avoidable healthcare cost,” said Dr.
Alauddin Bhuiyan, the founder and CEO of the company.
The company is currently in the final phase of clinical trials and working on
FDA clearance for these indications and others.
iHealthScreen company is open to partnership within its products. For more
About iHealthScreen Inc.
iHealthScreen (iHS) Inc. was established in 2015. With NIH SBIR funding in
excess of $2.5M, the company has developed iPredict^TM, an AI and
telemedicine-based HIPAA compliant software product for automated screening
and prediction of individuals at risk of developing age-related macular
degeneration (AMD), diabetic retinopathy (DR), glaucoma, Cardiovascular Heart
Disease and stroke.
View source version on businesswire.com
Alauddin Bhuiyan, Ph.D.
CEO, iHealthScreen Inc.
T: +1 718 926 9000