Stanford Medicine and Oxford University have partnered to unpack the role of big data in biomedicine, to be discussed at a conference in the US at the end of May.
The Big Data in BioMedicine Conference will bring together thought leaders looking to extract value from the growing volume of biomedical data, and in doing so, to transform the diagnosis, treatment and prevention of disease, say the organisers.
"We're bringing together people from academia, industry, government and foundations who want to learn more about how big data can drive innovation for a healthier world," says Stanford systems medicine chief Atul Butte, who is also the conference's scientific programme committee chair.
"We expect that attendees will walk away from this with a strong understanding of the latest tools and technologies available for studying and using big data in biomedicine; of where the unmet medical needs are and how they can be addressed with these approaches; and of what the tractable next steps are that they can take to become innovators."
According to Butte, this kind of conference is relevant in light of the incredible amount of data society is producing each day. In a special report by the Stanford School of Medicine, Butte discussed how the exponential growth in data means we need to look at science in new ways, going on to say that many of the answers to important medical questions already exist, but are trapped inside a matrix of voluminous data gathering dust in myriad repositories.
"Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world," he says, adding that it is up to scientists to share this data. Using specialised systems, data mining and algorithms, medical researchers can access massive amounts of data, saving them time and money, and potentially saving lives, he says.
"Data is power. It is revolution. It is frozen knowledge that requires you and I to bring the light and energy to let that knowledge free," he says.
The Big Data in BioMedicine Conference will be held from 22 to 24 May at the Stanford School of Medicine's Li Ka Shing Centre for Learning & Knowledge.
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