Artificial intelligence and machine learning took hold in healthcare during 2017

This year was a fun one for futurists, sci-fi fans and health IT professionals fascinated by artificial intelligence, cognitive computing and machine learning. The excitement started building ahead of HIMSS17 in Orlando and the show floor was abuzz with AI talk -- much the way pop health dominated the discourse at HIMSS16 and HIMSS15 before that. Several things became clear this year: AI is real and it's here with 86 percent of hospitals using some form of it and others like NewYork-Presbyterian already embarking on significant projects, there are two types of machine learning to understand now (those being supervised and unsupervised), and machine learning engineers are among the hottest emerging careers, and early practical applications include claims collection, clinical decision support, cybersecurity and radiology, just to name a few. AI this year also sparked questions about ethics and emotional intelligence, notably that hospitals and companies outside healthcare need to create standards, obligations and metrics before deploying the technologies. If a machine learning algorithm can be proven more effective than humans at reading radiological images will it be unethical to continue letting people do that job?