'Google search algorithm helps track spread of cancer'
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The equations search engine Google employs to predict the Web pages its users visit has inspired a new way to track the spread of cancer cells in the human body.
"Each of the sites where a spreading, or metastatic, tumour could show up are analogous to Web pages," said Paul Newton, a mathematician at University of Southern California.
Google ranks Web pages by the likelihood that an individual would end up visiting each one randomly. These predictions are based on the trends of millions of users across the Web, the 'Live Science' reported.
It uses the "steady state distribution" to calculate the probability of someone visiting a page.
"You have millions of people wandering the Web, [and] Google would like to know what proportion are visiting any given Web page at a given time.
"It occurred to me that steady state distribution is equivalent to the metastatic tumour distribution that shows up in the autopsy datasets," Newton said.
The referred dataset contains information about autopsy patients from the 1920's to the 1940's, who died before chemotherapy was available.
By focusing on this group of patients, the researchers could track the natural progression of cancer, specifically lung cancer, without different treatments interfering with the data.
Out of fifty metastasis sites described in the autopsy reports, the scientists found that twenty-seven contained cancer that appeared to have spread from the lungs.
Just like with an individual browsing the Web, cells that break off from the original lung tumour and entered the bloodstream had a certain probability of progressing to
Following the Google's example with search results, the researchers split the sites where the lung cancer spread to into two groups into first and second order.
In first order sites, tumour cells would most likely reach them by travelling directly from the lung. Tumours are more likely to reach second order sites by colonising a first order site and then spreading to the second order location.
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