MAY 13, 2015 7:30 AM PDT

Keynote: Big Data in Health Care and Biomedical Research

Speaker
  • Professor of Computational Biology and Bioinformatics, Chair of the Department of Biostatistics, Harvard University, Dana-Farber Cancer Institute
    BIOGRAPHY

Abstract

Every major scientific and technological revolution in history has been driven by one thing: access to data. Today, the availability of Big Data from a wide variety of sources is transforming health and biomedical research into an information science, where discovery is fueled by our ability to effectively collect, manage, analyze, and interpret data, and where Improving outcomes and controlling cost require effective use of available information. Realizing Big Data’s full potential will require that we develop new analytical methods to address a number of fundamental issues and that we develop new ways of integrating, comparing, and synthesizing information, and that we develop approaches that allow us to communicate want we learn in an intuitive and useful fashion to a variety of “consumers” each of whom has unique needs for data access. If we are successful, we have the opportunity to both dramatically improve our understanding of human disease and to implement protocols that will ultimately help to contain costs. Using concrete examples from our work, I will present some vignettes that highlight the challenges and opportunities that present themselves in today’s data rich environment in health care and biomedical research. Learning Objectives: 1. Understand the key opportunities 2. Identify some of the challenges inherent in the use of Big Data in health and biomedical research.


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MAY 13, 2015 7:30 AM PDT

Keynote: Big Data in Health Care and Biomedical Research


Specialty

T-Cells

Cancer Diagnostics

Cancer

Dna

Cell Culture

Cancer Research

Biomarkers

Immunology

Gene Expression

Clinical Diagnostics

Tumor

Biotechnology

Infectious Disease

Functional Medicine

Therapy

Geography

Asia50%

Europe50%

Registration Source

Website Visitors100%

Job Title

Student50%

Engineer50%

Organization

Academic Institution100%


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