Problems With Data in the Healthcare Industry
Common Problems and Pitfalls While Working with Data from the Healthcare Industry
It is expected that AI Healthcare market will grow to $27.6 billion by 2025 [1]. Healthcare AI-assisted products that are being developed by startups are becoming more popular and are commonly used in clinics, hospitals, or homes. Some of the most interesting solutions offered by these businesses include AI-powered health assessment (Babylon Health), early cancer detection using machine learning (Freenome), or AI-powered wearable devices to assist blind people (OrCam).
To develop those AI-assisted products, it is necessary to have a lot of high-quality data relevant to the problem that you want to solve in the healthcare market. The data in healthcare poses some challenges and risks which can effectively smash your business idea into pieces.
In this article, I will describe common problems and pitfalls that I discovered while working with healthcare data as a research intern in IT Innovation Centre. Let’s get started!
