An article entitled “Artificial
Intelligence Uses Biggest Disease Database to Fight Cancer,” written by Bissan
Al-Lazikani, is showing that artificial
intelligence is doing exactly what the title says it is doing: fighting cancer.
Technology is able to gather huge quantities of data about cancer. Databases
that have all this information about the genetic profiles of tumors and other
things can potentially mean new drugs. “The International Cancer Genome
Consortium is profiling up to 20,000
cancer patients already and the world’s largest single database of cancer
patients has just
been launched. It will combine near real-time cancer data on the 350,000
cancers diagnosed each year in England, along with detailed clinical
information and over 11m historical cancer records. With all this information,
you might expect new breakthroughs in cancer treatment to come in thick and
fast. But the more of these goldmines of raw material we have, the harder it
actually becomes to make sense of it.”
The author says that previous
sentence in the article. It is a great thing that there is a profiling of so
many cancer patients and that we can see what these cancers are made of.
However, it still going to be a tough task to take these cancer records from
people in England and applying them to other people.
Here is an explanation of the
database they are using to help them with this cancer research:
“To make this easier we’ve
developed a unique canSAR database to
link the raw goldmines of genetic data to a whole raft of independent
chemistry, biology, patient and disease information. It collates billions of
experimental results from around the world including ones on the presence of
genetic mutations, the levels of genes and their resultant proteins in a
tumour, and the measured activity of a compound or drug on tested proteins.
The system then “translates” these
data into a common language so that they can be compared and linked. It can
even explore the patterns of interaction between proteins in a cell using
similar systems that are used to explore human interactions in social networks.
Once these masses of data are collated and translated, canSAR then uses sophisticated
machine learning and artificial intelligence to draw paths between them,
predict risks and make drug-relevant suggestions that can be tested in the lab.”
The author says it is like trying
to predict the likely winners of a 100m Olympic race. Certainly not an easy task
by any means, but it can be right sometimes. That is how people are able to
predict anything. They look at patterns. They notice the consistencies in the
data. That is what the artificial intelligence in these machines will do. These
things will make it easier to do because they are machines and work quicker
than humans do. If these machines can pull this off and find cures for cancer,
then artificial intelligence may be moving quicker than I thought it could.
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