Machine learning can bring more intelligence to radiology

Machine learning is emerging as one of the key hopes to change the practice of radiology--the opportunity seems ripe, with rising calls for radiologists to demonstrate increased quality and more value, even as technology yields bigger datasets and more complexity. But exactly how machine learning will impact the radiology profession--and healthcare in general--remains to be seen. It will just take time and experimentation with machine learning, some say. Keith Dreyer, DO, likens the machine learning revolution to the promulgation of electricity, which originally was used simply for lighting, but eventually ushered in a host of helpful inventions--washing machines, dishwashers, air conditioners, televisions, computers--that were previously unimaginable. "Once you start to make machines think, taking data and performing predictive analytics, things will happen that are beyond human capability and current imagination," said Dreyer, vice chairman of radiology at Massachusetts General Hospital and associate professor of Radiology at Harvard Medical School. "So if you could predict a group of patients that are likely to have a positive CT of the brain before it was performed, think of the advantage that would be."