Workshop on Data Science, Learning, and Applications to Biomedical and Health Sciences

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This proposal requests funds to hold the Workshop on Data Science, Learning, and Applications to Biomedical and Health Sciences with the New York Academy of Sciences. The meeting will bring together experts from the areas of computer science, health and medical research. Health research and healthcare have undergone a decade of evolution in the expansion of available electronic data. Notable among these areas are the digitization of electronic health records, the aggregation of research and development data into databases by pharmaceutical companies and the release of decades of stored patient data by the federal government for research purposes and the onset of patient-self tracking. Together, these unprecedented increases in data volume, variety, and velocity, collectively termed 'Big Data', present a unique opportunity to gain insights, derive knowledge and foster discovery that will result in improved patient outcomes, reduced costs and accelerated biomedical advances. However, effectively dealing with this massive information and enabling investigators to enhance its utility will require a multidisciplinary approach. Multiple capabilities must be applied in joint research programs to develop relevant questions, to design approaches to address those questions and to develop tools that can be disseminated to the entire scientific community to train tomorrow's researchers in working with big data. The scope of this workshop will span the following themes: neuroscience and cancer, and cardiovascular disease using data from multiple sources.The workshop is expected to have a significant impact the area of big data and health. The focus of the workshop is develop a big data research agenda for this area and enable connections and collaborations among scientists from academia, industry, and government, clinicians and investigators engaged in technology development, deployment, and use. Specifically, the workshop will provide a forum for these investigators to assess the state-of-the-art research in big data and health and identify related challenges. The workshop results are likely to include new research directions that will be identified by the participants will be publicized to the research community through publications and a workshop website. The results dissemination is expected to inform and motivate the big data in health research community, interdisciplinary collaboration, educational activities, and spur other innovative research directions. As noted above, the broader impacts of the meeting are to facilitate progress in the field and stimulate conversations, connections, and collaborations that will lead toward better informed and effective generation and use of big data in health research.