Talithia Williams, Harvey Mudd College | Stanford Women in Data Science (WiDS) Conference 2020
summary
Argues that individuals should collect and interpret their own health data to change behavior and inform medical decisions, using consumer devices like Fitbits and thermometers to produce actionable time series. Shows concrete examples: using daily waking temperature to pinpoint ovulation, using Fitbit step counts to move from a baseline to a 10,000-step goal, tracking resting heart rate to measure fitness gains, and reviewing historical labor charts to refuse a recommended C-section and have a successful natural birth. Flags privacy risks around DNA and company use of data.
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chapters (9)
- 0:00Intro
- 0:51Nova Wonders
- 2:03Data Mining
- 3:56Csection
- 5:30Boundaries
- 6:07Power in Numbers
- 7:51Advice for Women of Color
- 8:37How to Use Your Data
- 9:55Data Privacy
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