Deep learning algorithm diagnoses skin cancer as well as seasoned dermatologists
As MDs, I think it is very clear that all of us who understand even the slightest about computers and tech see that machine learning is the way to go. Medicine is ideally suited to ML, and in time, it will absolutely shine in that domain.Now for people eagerly awaiting the MDs downfall, I think you are precipitating things a bit. We all tend to believe in what we do, and I concur in saying that expert systems will replace doctor judgement in well-defined, selected applications in the decade to come. But thinking that the whole profession will be impacted as hard as factory workers, with lower wages and supervision-only roles, is not realistic. What will be lacking is the automation of data collection, because you seem to underestimate by far the technical, legal, and ethical difficulties in getting the appropriate feedback to make ML appliances efficient. I firmly believe in reinforcement learning, and as long as the feedback system will be insufficient, doctors will prevail, highly-paid jerks or not.I myself am an anesthesiologist, a profession most people think of as a perfect use case for those techs (as I do), and wonder why we haven't been replaced already. The reality is that the job is currently far beyond what an isolated system could do. We already have trouble in making cars follow the right lane in non-standard settings. I hope people realize that in each and every medical field, the number and complexity of factors to control is far greater than driving in the right lane.People who drive the medical system have no sense of technology. They cannot even envision the requirements for machines to become efficient in medicine. That is why we are seeing quite a lot of efficient isolated systems pop up, but we won't be seeing fully integrated, doctor-replacement systems for a long time. This will require a new generation of clinical practitioners, who will understand how to make the field truly available to machine efficiency.