You can Google almost any piece of info nowadays, and which could soon include when you will kick the bucket. The technology giant has partnered up with Stanford University to help test a brand new computer system to forecast the time-of passing of hospital patients. Using artificial intelligence, the techy types say the accuracy of their application is as far as 95 percent. It works by taking in personal data like age and ethnicity that is then united with hospital information as vital signs and any prior diagnoses. As the AI application is utilized increasingly more, it gets smarter in forecasting the death of the patient.

These models outperformed conventional, predictive models clinically used in all cases, clarified Google’s Alvin Rajkomar. The was trained through analysis of 160, 000 adult and kid patient files from Stanford University and the Lucile Packard Children’s Hospital. When the algorithm was implemented to 40, 000 active patients it was correct in ninety percent of cases. The scale of information available enabled us to build an all cause mortality prediction model, instead of being a disease or demographics specific, stated Anand Avati, a member of Stanford University’s AI Lab, reported IBTimes. Kenneth Jung, a research researcher at Stanford University said: We believe that maintaining a physician in a cycle and thinking of this as machine learning in addition to the physician is the way to go as opposed to blindly doing clinical interventions based on calculations. That puts us on a firmer ground both ethically and safety wise.