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Yes, you read it correctly Google's new Artificial Intelligence medical brain can predict patients death and health risks accurately than Doctors.
It shocked the Medical experts with its accuracy and algorithm. It has an accuracy rate of 95 percent which can be helpful in the medical sector in the future.
It diagnoses the patient's health risks and calculates the death time of the patients by the data collected from the patient's age gender and other factors.
In a case study of a woman with metastatic breast cancer, Google utilized its algorithm and 24 hours after she was admitted, Google predicted a 19.9 percent likelihood of her dying within the hospital. This is was in complete contrast with the 9.3 percent estimate that the hospital’s augmented Early Warning Rating (aEWR) predicted. The patient succumbed to death within 10 days of admission.
The incident was rather harrowing but has convinced and impressed medical experts. Mostly because Google's systems have the ability to go through the data which was previously out of reach, for instance, notes buried in PDFs or scribbled on old charts. Manual reach takes tremendous amounts of time, and the hospital's internal systems cannot sift through and comprehend this information.
Nigam Shah, who is the associate professor at Stanford University, was quoted as saying that nearly 80 percent of the time spent today in predictive models is for the "scut work", which involves making data presentable. However, Google's software approaches the issue differently.
"You can throw in the kitchen sink and not have to worry about it," Shah told Bloomberg.
What medical experts found most interesting and innovative was the algorithm's ability to access and assess data that could not be used earlier, like notes hidden in PDF files, and scribbles on old charts.
Is this can be a future of medical science let us know in the comments.
Thank you
TOsTech Team
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It shocked the Medical experts with its accuracy and algorithm. It has an accuracy rate of 95 percent which can be helpful in the medical sector in the future.
It diagnoses the patient's health risks and calculates the death time of the patients by the data collected from the patient's age gender and other factors.
In a case study of a woman with metastatic breast cancer, Google utilized its algorithm and 24 hours after she was admitted, Google predicted a 19.9 percent likelihood of her dying within the hospital. This is was in complete contrast with the 9.3 percent estimate that the hospital’s augmented Early Warning Rating (aEWR) predicted. The patient succumbed to death within 10 days of admission.
The incident was rather harrowing but has convinced and impressed medical experts. Mostly because Google's systems have the ability to go through the data which was previously out of reach, for instance, notes buried in PDFs or scribbled on old charts. Manual reach takes tremendous amounts of time, and the hospital's internal systems cannot sift through and comprehend this information.
Nigam Shah, who is the associate professor at Stanford University, was quoted as saying that nearly 80 percent of the time spent today in predictive models is for the "scut work", which involves making data presentable. However, Google's software approaches the issue differently.
"You can throw in the kitchen sink and not have to worry about it," Shah told Bloomberg.
What medical experts found most interesting and innovative was the algorithm's ability to access and assess data that could not be used earlier, like notes hidden in PDF files, and scribbles on old charts.
Is this can be a future of medical science let us know in the comments.
Thank you
TOsTech Team
Follow us on social media and be a part of our social media family.
Like our Facebook page
https://goo.gl/2kaXBc
Subscribe us on YouTube and help us grow
https://goo.gl/BQuUy3
Follow on the Instagram account
https://goo.gl/LVWUQ5
Also, Read And Follow our Blog
https://goo.gl/55WrBR
Follow on LinkedIn -
https://goo.gl/tXXfAy
Thank u and keep supporting
- TOsTech team
stay connected stay techy
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