HOW WE BUILT AI-POWERED HEALTHCARE APPLICATION FOR DIAGNOSTIC IMAGING INDUSTRY
What started in distant corners of human imagination caught on like wildfire drastically reshaping today’s reality. Think of self-driving cars, cybernetic limbs, smart personal assistants, AI-powered customer assistants, autonomous drones, smart home devices etc. As AI technology gets more adaptable, the public attention it generates and the media coverage it gets is only beaten by the healthcare news headlines reporting huge death rates. AI technology has been summoned up to stem the tide.
Our team joined forces with our client who pursued a lofty goal to apply machine learning algorithms, utilize AI technology for big data analysis and develop an image-based deep learning system aimed at estimating the risk of breast cancer and diagnosing oncology at the earliest stage.
We will walk you through the stages of this idea development into a software solution.
Over the past years medical imaging techniques (X-rays, MRIs, etc) have advanced in relevant representations of tissue abnormalities and are now commonly used in healthcare, creating a vast amount of data radiologists sift through daily. With a steadily increase in the amount of imaging data often being the cause of a delay in diagnosis, radiologists would look to software to improve workflows and diagnostic accuracy of medical imaging interpretation. The tech solution would also prevent the professional burnout of medical specialists who daily struggle through a maze of data.
Building a medical image interpretation system with a capability to retrieve and interpret data and identify the likelihood of breast cancer meant addressing the following issues:
- Adapting the system for collaboration with humans
- Building the system for processing large volume of data
The machine learning project comprised three stages:
- Back-End development with .NET framework
- AI technology integration
Read more at our website: https://agiliway.com/building-ai-powered-healthcare-application-for-diagnostic-imaging-industry/