I had a go using the Watson cancer decision making system. This was the experience: Web interface. Log in. Add new patient. Fill in many many different check bo

I had a go using the Watson cancer decision making system. This was the experience: Web interface. Log in. Add new patient. Fill in many many different check boxes/drop down lists about the patient. Some of these seem irrelevant. Push a button. Treatment recommendations come up. Top recommendation is reasonable. Evidence summary provided about the recommendation. This is explicitly marked as being human curated from the MD Anderson, not generated by Watson. Links to possible clinical trials given - these were wrong, not applicable to the patient at all. So in summary, this is really designed for a doctor treating a cancer that they aren't really used to treating. There is no 'magic' that I could see. Maybe I used the most simplistic version, but the major limitation seems to be that it requires very structured input about the patient's case. I can't indicate for example that there was something unusual about the how the cancer looked under the microscope, or that the patient has a rare other medical condition that influences the treatment decision etc. Not surprising, because these are factors that lack an evidence based recommendation. If you read the article this is the key point: "I see technology like this as a way to really break free from our current health-care system, which is very much limited by the community providers. If you want expert care you have to go to an expert center," she said, "but there are never enough of those to go around." This is quite a different goal to 'revolutionising' cancer care, or 'taking on' cancer. There is clearly a lot of hype... But I laud the effort, it will likely end up being genuinely useful in the future. At the moment it seems to be a very thin machine learning layer on top of a highly domain-customised infrastructure.