Radiologists say that using AI can make their practice better without rendering them obsolete. Artificial intelligence conjures up scenarios of robots building other robots or self-driving vehicles putting truck drivers out of work. But these days, IBM's Watson computer is just as likely to interpret a CT scan, using AI to revolutionize radiology and other medical fields. Researchers believe AI will not put human radiologists on the endangered species list anytime soon, if ever. But AI and deep learning offer speed, accuracy and consistency to extend the capabilities of human imaging professionals.
Algorithms based on machine learning and deep learning, intended for use in diagnostic imaging, are moving into the commercial pipeline. However, providers will have to overcome multiple challenges to incorporate these tools into daily clinical workflows in radiology. There now are numerous algorithms in various stages of development and in the FDA approval process, and experts believe that there could eventually be hundreds or even thousands of AI-based apps to improve the quality and efficiency of radiology. The emerging applications based on machine learning and deep learning primarily involve algorithms to automate such processes in radiology as detecting abnormal structures in images, such as cancerous lesions and nodules. The technology can be used on a variety of modalities, such as CT scans and X-rays.
In what was perhaps one of the most memorable openings in literature in English, Charles Dickens began his immortal A Tale of Two Cities with this: "It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of light, it was the season of darkness, it was the spring of hope, it was the winter of despair, we had everything before us, we had nothing before us, we were all going direct o heaven, we were all going direct the other way--in short, the period was so far like the present period, that some of its noisiest authorities insisted on its being received, for good or for evil, in the superlative degree of comparison only." And yes, that was one long, run-on sentence….!
"We're definitely right in the eye of the storm of the hype cycle," Rasu Shrestha, M.D., chief innovation officer at University of Pittsburgh Medical Center, told SearchHealthIT on the busy "technical exhibition," or show, floor. "Having said that, that hype is being driven by an immense amount of hope. Could AI and machine learning solve for the complexities of healthcare?"