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【Master Forum】Data Science Meets Medicine

  • 2017.02.16
  • Event
Data Science Meets Medicine: Translating Biomedical Research into Precision Healthcare

Topic: Data Science Meets Medicine: Translating Biomedical Research into Precision Healthcare

Speaker: Brian D. Athey

Date: February 17, 2017, Friday

Time: 16:15- 17:30

Venue: Governing Board Meeting Room, Daoyuan Building

Language: English

Speaker Profile:

Brian D. Athey, Ph.D.

  • Michael A. Savageau Collegiate Professor and Chair
  • Department of Computational Medicine and Bioinformatics
  • Professor of Psychiatry and Internal Medicine
  • University of Michigan Medical School
  • Co-Director
  • Michigan Institute for Data Science (MIDAS)


Data Science is the key underlying methodology that is rapidly accelerating and transforming science and technology worldwide. Nowhere is this truer than in biomedical research and healthcare--largely because these fields have been resistant to computerization, mathematics, and statistical analysis. In this talk, I will review the fundamental principles of Data Science, its scope, and its promise to transform biomedical research and healthcare delivery into precision health care that will positively impact individual and population health outcomes. Specifically, I will review:

  • The biomedical “Big Data Tsunami”, its structure and characteristics, and the emergence of “Data Integration”
  • What are Data Science and Analytics, and what are the opportunities for biomedical research and healthcare?
  • A general model for how applications and data science methods synergize with each other
  • What is personalized medicine and healthcare?
  • Emerging driving examples: Single Cell Analysis, Analysis of the Longitudinal Electronic Health Record (EHR), Pharmacogenomics, Critical Care Phenotyping, the Medical Microbiome, and Neuroimaging, from the 1000 Genome Project to a ‘Million Genomes’
  • Extending the vision to the home
  • Rethinking Health IT Infrastructure beyond the Electronic Health Record--Platform and personnel considerations
  • Open Source and leveraging community applications science expertize
  • Health Econometrics
  • The promise of individualized care and its potential impact on Public Health

Keywords: Data Science, Big Data, Data Integration, Analytics, Precision Medicine, Healthcare, Personalized Medicine, Genomics, Phenome, Electronic Health Record (EHR), Health IT, Open Source, Health Econometrics, Public Health