The growth of analytics capabilities and artificial intelligence have raised expectations and the need for good data management and data quality. But how can challenges in multimodal data integration be solved, with the exponential growth of data volume, velocity, and variety, and close auditing of veracity?
Read thoughts from Costas Tsougarakis, Flywheel VP of Life Science Solutions, in Genetic Engineering & Biotechnology News.
“When analyzed properly, scans from different imaging modalities—X-ray imaging, magnetic resonance imaging, computed tomography imaging, and so on—can be applied to better characterize disease mechanisms and therapeutic responses, thereby improving predictive models. Such approaches can inform clinical trials by supporting patient-related decisions, such as selection and classification, and novel biomarkers that can become objective study endpoints.”
Read the full article to learn how to meet expectations for good imaging data management and shift organizational mindsets to store high-quality data for analysis and reuse.