The report talks about a woman who was suffering from breast cancer and got a radiology scan done after getting admitted to a city hospital. It is worth mentioning that her cancer was in a late stage and fluids had already filled her lungs when she came to the hospital. Seeing her vital stats, the computers at hospital predicted a 9.3% for chance of her dying during her stay. Google differed the assessment. The technology giant’ algorithm assessed the woman and estimated the chance of her risk at 19.9%. And Google was proven to be right, as the woman passed away just 10 days after being admitted. Google published the story of this woman in May this year in its research and highlighted how neural networks can be used in the field of health-care. For those who don’t know, neural networks are a kind of artificial intelligence that learns and improves by using data. The report further says that medical experts are impressed by Google’s technology because of the access it had to data that was previously not available. It is even considered to be faster and more accurate than the techniques that are currently being used. Google’s technology actually makes the machines to parse data and the neural networks not only collect data for predictions, but also showcase it to add credibility to them. The current methods of mining health data, according to the report, are expensive, cumbersome and also consume time. Nigam Shah of Stanford University, who co-authored Google’s research said that the methods deployed today spend 80% time in ‘scut work’ of making data presentable. Google’s approach is said to avoid this. According to Bloomberg, AI chief Jeff Dean said in revealed in May this year that in its next steps, the technology giant wants to bring its system to clinics. Google has been focussing a lot on artificial intelligence since the last few years and with these advancements, the company can foray into a new market. However, implementation of this will surely be a challenge, moreover because it will mean giving machine learning a lot of control over which patient should get what care and when somebody would die. Earlier, IBM Watson has also tried integrating artificial intelligence and medical science, but the company had a very tough time doing it.
