Integrated Data Analytics Use Cases

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