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Big Data in Biomedicine

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Published on May 21, 2015

The Urgent Need for Data Wrangling, Data Mining and Visualization Tools and Expertise

by Sean Mooney, PhD, Chief Research Information Officer, University of Washington Medicine and also Professor, Department of Biomedical Informatics and Medical Education, University of Washington, Seattle

The healthcare clinical enterprise is currently facing a flood of data that has become an ocean of complexity and challenge. Along with this, there has become an urgent need for data science and analytics in biomedical research. The University of Washington Medical Center and its partners are no stranger to this digital world. With four hospitals, more than 20 primary care clinics, nearly 270 specialty clinics, 9 urgent/emergency care centers, 20+ pharmacies, and a trauma center that serves Washington, Alaska, Montana and Idaho, our data research and analytics needs are complex and potentially highly impactful. In this presentation, I will give an overview of the data challenges we face in research from basic to clinical medicine. I will present the need for data wrangling expertise, visualization tools and data mining methods including natural language processing, graph theoretic approaches and machine learning. I will also describe the challenges around clinical data research including data governance, security and the ethical use of human subjects data. As a Python developer since 1996, I will highlight successes as vignettes and current trends in Python tools in biomedical research applications. Finally, I will look toward the future where patients and their healthcare are even more tightly connected through mobile health applications, advances in electronic health record technologies and the emergence of precision medicine.

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