Integrated Data Analytics Use Cases

Machine Learning (ML) of massive biomedical data offers both untapped potential and significant challenges, for enhancing biomedical discovery, healthcare delivery, diagnosis, and outcomes. BioSymetrics takes a unique approach to end-to-end ML, where relevant data-type specific pre-processing enables integration and analysis on multiple datasets in combination. Our feature selection methods leverage a powerful iteration framework that make our models more robust and more effective, delivering results with unprecedented speed and accuracy. Below, we present examples of AI ML in the context of discovery research and diagnostics, for improved predictive outcomes in comparison to analytics of one data type only.