A number of different data streams (e.g. imaging, pathology, genomics, electrophysiology) are routinely acquired in the clinic for disease characterization. However most of this acquired “Big Data”, which contain cues on disease behavior and patient outcome, remains largely under-exploited and un-interrogated. The paucity of analytic and biomedical informatics tools to collectively harness and hence “unlock” quantitative, disease related insights from Big biomedical data, has often led to calls for better, higher resolution technologies or additional tests. However, much value and knowledge remains to be gained from routinely acquired clinical Big Data, including deeper insights into disease processes and mechanisms. This is especially true at a time of spiraling health care costs, where the need of the hour is “faster, cheaper, and better” and to maximize mileage from “standard of care” data.

Health informatics is a rapidly emerging that applies computer and information science to health sciences research, education, and patient care.

Biomedical informatics is a cross-cutting, interdisciplinary field that identifies, explores, and implements effective uses of data, information, and knowledge to improve the decision-making and problem-solving efforts to improve human health. The discipline of Big Data analytics and health Informatics is a rapidly growing strategic focus within the department of Biomedical Engineering at CWRU. Faculty and students are involved in developing and applying a variety of Big Data analytic tools to imaging, digital pathology, genomics, proteomics, and electrophysiological data with the goal of assisting physicians solve clinical translational problems.