Mediwhale, Inc.
Mediwhale is an innovative healthcare startup founded in 2016 that leverages AI-powered diagnostic solutions using non-invasive retina scans to predict and prevent diseases such as cardiovascular, kidney, eye diseases, and biological aging. Their mission is to bridge the healthcare gap by making preventive care accessible, affordable, and effective through advanced retinal AI scans, empowering early detection and personalized health assessments.
Industries
Nr. of Employees
small (1-50)
Mediwhale, Inc.
Seoul, Seoul-t'ukpyolsi, South Korea, Asia
Products
Retina-based cardiovascular risk assessment software (SaMD)
Software medical device that analyzes fundus photographs to estimate future cardiovascular disease risk and a retinal proxy for coronary artery calcium, intended as a non-invasive adjunct to traditional risk tools.
Retina-based chronic kidney disease risk prediction software (SaMD)
Software that analyzes retinal photographs to estimate personalized future risk of chronic kidney disease, intended to identify high-risk patients non-invasively.
Retina-based eye disease screening software (fundus screening)
Automated classification of fundus photographs to detect referable eye diseases such as glaucoma, cataract-related media opacity, age-related macular degeneration and diabetic retinopathy, with referral recommendations.
Retina-based biological age estimation software (SaMD)
Algorithmic estimation of biological age and associated mortality/morbidity risk from retinal vessel features to support risk stratification and lifestyle counseling. Validation studies include longitudinal cohort analyses and have demonstrated association with incident COPD in UK Biobank.
Retina-based cardiovascular risk assessment software (SaMD)
Software medical device that analyzes fundus photographs to estimate future cardiovascular disease risk and a retinal proxy for coronary artery calcium, intended as a non-invasive adjunct to traditional risk tools.
Retina-based chronic kidney disease risk prediction software (SaMD)
Software that analyzes retinal photographs to estimate personalized future risk of chronic kidney disease, intended to identify high-risk patients non-invasively.
Retina-based eye disease screening software (fundus screening)
Automated classification of fundus photographs to detect referable eye diseases such as glaucoma, cataract-related media opacity, age-related macular degeneration and diabetic retinopathy, with referral recommendations.
Retina-based biological age estimation software (SaMD)
Algorithmic estimation of biological age and associated mortality/morbidity risk from retinal vessel features to support risk stratification and lifestyle counseling. Validation studies include longitudinal cohort analyses and have demonstrated association with incident COPD in UK Biobank.
Services
Point-of-care retinal AI screening deployment (SaaS)
Deployment and integration of cloud-hosted retinal image analysis software in clinics and hospitals, including compatibility with common fundus cameras, operator training, and on-going technical support.
Clinical research and validation support
Collaboration on study design, data access and analysis for clinical validation and publication of image-derived biomarkers and diagnostic algorithms; support for regulatory study submissions.
Point-of-care retinal AI screening deployment (SaaS)
Deployment and integration of cloud-hosted retinal image analysis software in clinics and hospitals, including compatibility with common fundus cameras, operator training, and on-going technical support.
Clinical research and validation support
Collaboration on study design, data access and analysis for clinical validation and publication of image-derived biomarkers and diagnostic algorithms; support for regulatory study submissions.
Expertise Areas
- Retinal image–based AI diagnostics
- Clinical validation and cohort study execution
- SaMD development and cloud deployment
- Medical device regulatory strategy and reimbursement
Key Technologies
- Deep learning for medical imaging (convolutional neural networks)
- Fundus (retinal) photography
- Cloud-based image analysis and reporting
- Model training on multi-cohort longitudinal datasets