The Future of Diagnostics: Machine Learning Healthcare App Development

In recent 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. The number of images can be overwhelming to process which often leads to delay in diagnosis or even professional burnout of radiologists. With a steadily increase in the amount of imaging data radiologists would look to the AI app to improve workflows and diagnostic accuracy of medical imaging interpretation. 

Our client pursued a lofty goal to develop an AI-based healthcare application that would expedite the transition from curative to preventative healthcare. The core idea was to apply machine learning algorithms for big data analysis and develop an image-based deep learning system for estimating the risk of deseases and diagnosing oncology at the earliest stage.   

 

Complex business logic defined the required web application behavior and functions. For this reason, the healthcare solution was built as a multiple-module system, where each module, incorporated through the interface, served a separate business function. 

The full case you can READ HERE.