Use cases: Machine Learning Solutions
As technology progresses, new tools and devices are introduced into the healthcare sector. This also means that increasingly larger data sets are being collected, which can be fed into Machine Learning models for further analysis. With their help, healthcare professionals can diagnose more accurately, improve patient care and the safety of medical procedures, develop new treatments, as well as reduce long-term costs.
Analyzing large amounts of documents (e.g. patient records or SmPCs) automatically
Medical documents are usually repetitive and often include personal or sensitive data. Analyzing them manually is a tedious task requiring expert knowledge but an Optimal Character Recognition system can digitize handwritten texts for easier further processing and Information Extraction models can easily find the key pieces of information in them.
Supporting R&D activities by automated image analysis and faster experiment cycles.
As technology advances, medical imagery is getting more complex. In order to speed up experiment cycles, their analysis can be automated. Using Computer Vision methods, the analysis is not only quick, but also accurate and unbiased. Due to their pattern recognition capabilities, they can also gain insight that is not accessible by traditional means.
Improving efficiency and accuracy of medical diagnosis by automatic analysis of imaging techniques (e.g. X-Ray or MRI)
Advanced Computer Vision methods have the capabilities to recognize and categorize objects and detect anomalies in images with a very high accuracy. As medical imagery is very complex and detecting subtle signs of illnesses is a task where accuracy is crucial, it has been a very active research field in developing and improving Computer Vision models.