Next-generation AI for frictionless visual telemedicine
Produce accurate skin assessments on patients using a detailed 5-step image analysis AI.
About Us
developed by a team of engineers and doctors from MIT, Harvard, and ASU
Luis Soenksin PhD
Serial entrepreneur and medical device expert. MIT and Johns Hopkins BME graduate currently acting as MIT’s first Venture Builder in Artificial Intelligence and Healthcare.
Omar Badri M.D
Serial-entrepreneur, Internal Medicine, Co-founder of Medumo - company to guide, track, triage and educate patients (acquired by Phillips 2019). Practices at Brigham and Women’s Hospital (BWH) and Harvard Medical School.
Alex Alimov
Full-stack Software developer +10Y Experience in Mobile IOS, Android, Cloud.
Product
5-step image analysis for accurate skin assessments
01
Image quality assessment
Every image is assigned a quality score to determine if an accurate analysis can be performed by automated algorithms
02
Body Location mapping
Visible body parts in submitted images are automatically recognized, mapped and tracked
03
Fitzpatrick skin type
Upon face detection, a skin color palette is recognized to calculate the average phototype of the patient. Other features such as age, sex and ethnic skin are automatically infered to facilitate reporting
04
Image-based Differential Diagnosis
Our pre-trained deep learning algorithm receives image crops from received photos and produces arank ordered by diagnostic probability across 250 diseases with visual presentations
05
Question-based Refinement
A short list of highly focused questions is selected based on the determined differential diagnosis. These questions are designed to improve diagnosis probability and work through the short list of possible diagnoses
