10 Ways We're Using Data to Fight Disease


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Preventing Cancer
A woman gets a mammogram at a hospital in Haute-Savoie, France. Recommendations for when to get mammograms have changed in recent years. BSIP/UIG via Getty Images

Not all cancers are preventable, but wouldn't you want to stop the ones that are? Screening for predisposition and early growth exists for cervical, breast, lung, prostate and colon cancers. But how do doctors determine guidelines on who should get screened, how often and when? The answer lies in big data.

The U.S. Preventative Service Task Force uses high-quality big data from large epidemiological studies to determine screening guidelines. For example, from studying the rate of false-positive cancer diagnoses in women in their 40s, the task force determined that getting mammograms before age 50 is unnecessary (unless there is a history of breast cancer in the family) [source: WebMD].

Pulling as much data as possible from cancer patients also teaches doctors about how cancers grow. The Oregon Health and Science University is undertaking trials of gene-sequencing thousands of cancer patients to learn more about how cancer formation occurs in different people so they can offer quicker diagnoses. The university even envisions being able to diagnose cancer within 24 hours by 2020, thanks to what they learn [source: Oregon Health and Science University].

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