'Machine learning' may contribute to new advances in plastic surgery

April 29, 2016 - With an ever-increasing volume of electronic data being collected by the healthcare system, researchers are exploring the use of machine learning--a subfield of artificial intelligence--to improve medical care and patient outcomes. An overview of machine learning and some of the ways it could contribute to advancements in plastic surgery are presented in a special topic article in the May issue of Plastic and Reconstructive Surgery, the official medical journal of the American Society of Plastic Surgeons (ASPS). "Machine learning has the potential to become a powerful tool in plastic surgery, allowing surgeons to harness complex clinical data to help guide key clinical decision-making," write Dr. Jonathan Kanevsky of McGill University, Montreal, and colleagues. They highlight some key areas in which machine learning and "Big Data" could contribute to progress in plastic and reconstructive surgery. Machine learning analyzes historical data to develop algorithms capable of knowledge acquisition.