From military applications to medicine, computation can be used to analyze images. Imaging and clinical experts Dineo Mpanya and Nqoba Tsabedze of the Charlotte Maxeke Johannesburg Academic Hospital in Johannesburg, South Africa, teamed up to describe the impact of machine learning on the interpretation of medical images, such as chest X-rays. Subtypes of machine learning, such as convolutional neural networks, “can identify subtle changes in chest X-ray films, and in some instances, the accuracy levels for diagnosing conditions, such as pneumonia, are equivalent or superior to that of clinicians,” the scientists note. “Unlike traditional statistical methods, where inferences are made based on the population studied, machine-learning algorithms mimic human cognitive processes when making decisions.”
In April 2018, the US Food and Drug Administration approved the first AI-based diagnostic, IDx-DR, which detects diabetic retinopathy in people with diabetes by analyzing retinal images. Machine learning will soon be applied to many other medical conditions, from cardiology to neurodegenerative diseases and beyond.