Google machine will tell when the patient dies
Google machine will tell when the patient dies
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Google is building a machine that tells when the patient is about to die. This Google search is going to make a big difference to the medical sector. It is a matter of the past when a woman in a US City hospital came to get her breast cancer treatment. Until then, two doctors saw her and scanned through radiology. 

The hospital's computer, while reading the symptoms of women, said that while living in the hospital, she has 9.3 percent chance of survival. Then came the turn of Google. A new type of algorithm created by the company was tried on women. Through this, Google found out that there is a 19.3 percent probability of a woman's death. That woman's death occurred in the next few days. 

Google had mentioned the death of the woman in a research paper printed in May and during this time the capacity of her neural network was told. This is an artificial intelligence software that develops your understanding by reading and understanding the data. This has affected medical experts the most, that Google has also gathered the data that had been suppressed in the old chart and PDF file for the last several years. 

Only after acquiring this information will the software patient predict how many days will die. This software predicts faster than current technology. The Google system also tells which record it is giving the result. In the coming days, its machine will bring Google to which the medical field will be rejuvenated. 

Hospital doctors and other healthcare providers have been struggling for better use of electronic health records and other patient data for many years. If the correct information is found only on time, the patient's life can be saved.

In this case, the medical worker will have to spend less time on the paperwork and he will be able to spend more time in taking care of the patient. Google's next step is to predict the symptoms and diseases beforehand. It is obvious that if Google continues to succeed in its next step, then this will be the biggest revolution in the medical field.

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