Google’s thinking of reading the user’s mind could help to know the spread of cancer
Last month, we published an article from the scientific research published in the journal Scientific reports that shows that there are single types of unknown laws that are controlling everything from the brain to the social networking to the Universal expansion. Recently, scientists proposed that the Google’s search algorithm is also very similar to the spread of cancer cells to the other parts of the body. This proposal also shows that there are single types of laws from the networking to the bodily activities.
“Each of the sites where a spreading, or “metastatic,” tumor could show up are analogous to Web pages,” Paul Newton, a mathematician at the University of Southern California, who has been working with cancer specialists at the Scripps Research Institute, said in a statement.
Google check the trends of millions of users to rank web pages and it uses “steady state distribution” to determine the likelihood of someone visiting a page. The Steady-State Distributions of Large Markov Chains represents the mathematical system of transitions from one state to another and the states could be finite or infinite.
“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,” Newton explained.
“It occurred to me that steady state distribution is equivalent to the metastatic tumor distribution that shows up in the autopsy datasets.”
He worked on the patients of cancer in the year from 1920’s to 1940’s, who died before the chemotherapy was available. He worked on them to check for the natural progression of cancer especially lung cancer. Out of 50 metastasis sites in the autopsy reports, scientists discovered that 27 contained cancer that came from the lungs. Here, they found similarity with the user browsing the Web. Cells move from the lung tumor site to the bloodstream and can go to different locations.
So, using Google’s example of users, the scientists separated the sites of the spread of lung cancer into two groups i.e. 1st order and 2nd order. 1st order sites are the places where cells move from the tumor cells in the lungs and the 2nd order sites are the places where cells move from the 1st order site after colonization. With this thinking, researchers were able to calculate the average time it takes the cancer to move to the other parts of the body. They found that the lymph nodes were the fastest places for cells to go from lung cancer followed by adrenal gland and liver. They also found that the cells take so long time to reach to the bladder and uterus. Often, it is so long that the patient could die before the cells reach there.
Although researchers were not able to check the numbers of the times when doctors noticed new tumor but they were able to see the number of tumors located in each new site, they put that information into the model and determine the progression.
The researchers are thinking on more focused datasets. “What we’re trying to do now is use this baseline model and make it patient specific, or at least subgroup specific to make more targeted predictions,” Newton said.
They are also working on the model to reduce the spread of the cancer cells to other sites.
Here we have a little hypothesis that the spread of cancer could also be detected by working on how the words or particular statements spread among the people. So, it means psychology could also help us to work on cancer treatment.