EyeToAI
Based in Israel, EyeToAi delivers a new method of early-stage oncology disease diagnostics
business challenge
Our client needed to build a system with a high-performance rate and implement AI and machine learning technologies to solve one of the hardest challenges in radiology. To make a correct diagnosis, the doctor must сonsider a large number of case studies that are growing exponentially. That causes mistakes and delays in treatment in addition to the constant pressure on doctors.
The latest clinical research solutions based on AI faces two problems – they are not optimized for collaboration with humans and lack vast amounts of structured data needed for machine learning.
Location:
Israel
Industry:
Healthcare
Partnership:
2016 - ongoing
Team size:
5 member
Team Location:
Ukraine, Chernivtsi
Technologies:
.NET, React.js, Mssql, Webpack, Redux.
product overview
A platform that increases the productivity and accuracy of medical imaging interpretation. The core idea is the integration of artificial intelligence into the radiologist’s workflow in a seamless and intuitive manner.
EyeToAi has two major benefits. First, it makes radiologists more efficient with its robotic workflow automation (chatbot). Second, it opens new potential markets (Asia) for medical imaging diagnosis by providing a language-neutral solution.
values delivered by our team
- a solution built with multiple modules system and complex business logic
- high performance system with integrated AI + ML technologies and high-level accuracy on given reports
- UI/UX improvements based on customers feedback and development process
Michiel Kolomenkin
CTO at EyeToAi
“ImproveIT team help us with a very responsible mission – creating a web application for hospitals and radiologists. The core idea is to make medical image interpretation more efficient and accurate by utilizing cutting-edge machine learning, artificial intelligence and data analysis tools. I can say that their communication is key. Their attention to detail is great, and they question us if they think it might be better to solve the issue in a different way. They really care about the product they’re building.”
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