PAW Healthcare examines the tactics and strategies that hospitals, public health organizations, pharmaceutical companies, and medical researchers use to harness the power of data science. Predictive analytics can help medical professionals reduce costs, improve outcomes, an increase patient satisfaction.
These keynotes are only three of the dozens of sessions and workshops at PAW Healthcare to help you apply these lessons to your own organization. Register now and save an additional $150 with code KDN150.
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Real World Data and the Transformation of Healthcare
Presented by Dr. Martin Kohn, Chief Medical Scientist, Sentrian (formerly with IBM Watson)
How analyzing real-world data from large numbers of patients over an extended time period is essential for achieving healthcare personalization. |
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Brain-Machine Interface Technology: Separating Hope from Hype
Presented by Wasim Malik, Ph.D., Director, Harvard/MIT Laboratory for Neuromotor Signal Processing
Can a predictive analytics framework enable us to reliably extract movement commands right out of the brain? Are motor brain-machine interfaces currently feasible both from clinical and economic standpoints? |

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Predictive Analytics, Genomics, and Precision Medicine - Separating the Hype from the Reality
Presented by Nephi Walton, Pediatrician/Genetics Fellow at Washington University School of Medicine, with Ken Yale, JD, DDS, Vice President of Clinical Solutions, ActiveHealth Management
Explore one of the first large-scale, replicable, population-wide studies applying advanced predictive analytics and genetic testing to more precisely target wellness interventions in an otherwise healthy population.
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A limited number of rooms are available at the New York Marriott Marquis, the Courtyard by Marriott Chelsea, and the Springhill Suites Marriott with special reduced rates for attendees who register and book rooms before Monday, October 3. Click to see all discounts available to PAW Healthcare attendees.
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Rising Media Inc.
211 E. Victoria Street, Suite E Santa Barbara, CA 93101
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