Netflix algorithms can help doctors treat cancer: research

The future of cancer treatment can be customized, as well as a list of personalized TV shows and movie recommendations.

Researchers have created a new tool for predicting how a disease can behave, based on the science behind Netflix’s algorithms.

Streaming services track a user’s viewing history. This history, performed via artificial intelligence (AI), finds patterns of how often a particular show is watched and whether the viewer points his thumb up or down. AI uses this data to generate personal recommendations.

“We believe we can predict how cancer may behave based on previously experienced changes in the genome, just as Netflix can predict what will indicate that it will choose the next glance.” And co-author of the study Ludmil Alexandrov of the University of California, San Diego said:..

Medical AI looks for “damages” in tumors by examining intracellular genetic data, more specifically chromosomes and DNA. That is, exactly where the cancer starts and stops.

Twenty-one common obstacles have been identified. This helps doctors better determine cancer treatment plans that better reflect the characteristics of the tumor by finding out where the cancer is progressing and where it is weak. Tumors with shattered and reshaped chromosomes have been found to have the lowest chance of survival.

AI has been tested in approximately 10,000 patients with more than 33 types of cancer.The results were published in Scientific journal nature..

Within the software SigProfiler Extractor, this technology is now available for free in the hope that other researchers will be able to broaden their “disability” list and move closer to creating personalized “cancer blueprints.”

Co-author Nisharan Pirei “To stay one step ahead of cancer, we need to predict how it will adapt and change. Mutations are a major driver of cancer, but much of our understanding is that of cancer. It focuses on changes in individual genes. “

He added that the medical community “misses the big picture of how to copy, move, or delete a vast range of genes without causing catastrophic consequences for the tumor.”

“Understanding how these events occur can help us regain our advantage over cancer.”

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