A large technical team is working upon computer system of Artificial Intelligence that will predict the death date of patient after getting admitted within 24 hours away in hospital. This is real stumble to know that Artificial intelligence are trying to get the prediction with 95% of exact accuracy.
It will be done after analyzing all the data about the patient like age, gender, and ethnicity. Getting all these information correctly with analytical view will give the accuracy of the death date with 95%.
After this analysis, the result is then observed and revised with the reports of previous diagnoses, present condition and lab check-ups. All these are properly analyzed and revised to get exact percentage from experts. The analysis is basically done on the reports, symptoms which are presently occurring and doctor’s notes about the patient.
After this Google took AI systems to use identified data of 216, 221 patients from two US medical institutes. This eventually says that Artificial intelligence had more 46 billion data to revise. By time passing artificial intelligence will have associated with the final result and most probably know when someone is going to die.
Nigham Shah the professor at Stanford, University of Chicago said that about 80% of development is time-based on predictive models by going on data make look presentable for the artificial intelligence. But now Google computing systems can give accurate results by eating all the related data about the patient’s date of death by using an exaggerated machine for learning.
The best part of the artificial intelligence computing systems is that it will not going tell you the date of death or whether you are going to live but it will also tell you the stay of the patient in hospital and his or her chances of getting readmitted.
“These types of methods will help to get more accurate prediction than traditional style or prediction” said Alvin Rajkomar. He also added that hospitals who are interested or willing to adopt this method will be able to take care of patients in more efficient way rather than those who are not knowing this AI computing system.