Thinking ‘Oat’ of the Box

September 9, 2019

Robert C. Miller, Jr. and our Marielle S. Gross, MD, MBE write about technology to resolve the ‘goldilocks data dilemma’

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More than a million Americans have donated genetic information and medical data for research projects. But how that information gets used varies a lot, depending on the philosophy of the organizations that have gathered the data

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Anonymized data sets are growing and it is becoming easier to identify individuals. Research-consent procedures must be updated to protect people from being targeted

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Sam Cavaliere, a San Diego tech worker, considers himself in average health, though the 47-year-old admits, “I can always stand to lose a little weight.” Like a lot of iPhone owners, he uses Apple’s Health app to keep track of his weight, his exercise routines and how many steps he takes in a day

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PRIM&R’s Elisa Hurley writes that we still need the term “subjects” because there are other circumstances in which using the term “participant” might not be fitting

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Machine-learning techniques used by thousands of scientists to analyse data are producing results that are misleading and often completely wrong.
Dr Genevera Allen from Rice University in Houston said that the increased use of such systems was contributing to a “crisis in science”

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For example, data about a mobile phone’s past location and movement patterns can be used to predict where a person lives, who their employer is, where they attend religious services and the age range of their children based on where they drop them off for school

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New biomedical techniques, like next-generation genome sequencing, are creating vast amounts of data and transforming the scientific landscape. They’re leading to unimaginable breakthroughs – but leaving researchers racing to keep up

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