Google has developed an artificial intellegence algorithm that could predict when you will die with up to 95% accuracy, according to the tech giant's researchers.
The research, which tackles a range of clinical issues among hospital patients, was recently published in the journal Nature. Google applied artificial intelligence to a vast amount of data from more than 216,000 adult patients hospitalized for at least 24 hours each in two medical centers.
The research tapped into data from Electronic Health records.
In one major case study in the findings, Google applied its algorithm to a patient with metastatic breast cancer. 24 hours after she was admitted, Google gave her a 19.9% chance of dying in the hospital, in contrast with the 9.3 estimate with the hospital's augmented Early warning Score. Less than two weeks later, the patient died on her condition.
This isn't the first time Google's AI has been applied to predictie health care. Earlier this year, Deep-mind partnered with department of Veterans Affairs to feed its AI 700,000 medical records in order to predict deadly changes in patient medical condition.
The company is also working to develop a voice recognition system for clinical notes which will eliminate the need for doctors to type them in. In that particular case ,the challenge comes from inaccuracy -even the smallest mistake in patients record can result in them getting the wrong care. Dr. Steven Lin, who spread-headed the research with Google, told CNBC.
If Google can both smooth the process of entering data and improve the means by which that data is used, it could cut down on human error in medical care.....
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The research, which tackles a range of clinical issues among hospital patients, was recently published in the journal Nature. Google applied artificial intelligence to a vast amount of data from more than 216,000 adult patients hospitalized for at least 24 hours each in two medical centers.
The research tapped into data from Electronic Health records.
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In order to come to that number, the AI tallied 175,639 data points from the patient's electronic medical records, including handwritten notes. According to the paper, this is the difference between google's work and previous deep learning approaches.
In this whole study, Google analyzed 216,221 hospitalizations with 114,003 patients - and over 46 billion data points from all of their health records.
This isn't the first time Google's AI has been applied to predictie health care. Earlier this year, Deep-mind partnered with department of Veterans Affairs to feed its AI 700,000 medical records in order to predict deadly changes in patient medical condition.
The company is also working to develop a voice recognition system for clinical notes which will eliminate the need for doctors to type them in. In that particular case ,the challenge comes from inaccuracy -even the smallest mistake in patients record can result in them getting the wrong care. Dr. Steven Lin, who spread-headed the research with Google, told CNBC.
If Google can both smooth the process of entering data and improve the means by which that data is used, it could cut down on human error in medical care.....
Have a Great Day ahead.....💗💗💗💗
And please share this blog and subscribe to this website for more technical stuff....
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