Computer vs human: Deep learning versus perceptual training for the detection of neck of femur fractures

Single detection tasks in radiology are commonly used in DCNN research with their results often used to make broader claims about machine learning being able to perform as well as subspecialty radiologists. This study suggests that as impressive as recognising fractures is for a DCNN, similar learning can be achieved by top-performing medically-naïve humans with less than 1 hour of perceptual training.