Continuous advancements in technology are starting to fuel discussions about how machines will eventually replace humans. This line of thinking has reached even the medical field, as innovations in radiology continue to prop up the belief that radiologists will one day lose their jobs to AI-driven technology.
The concept of machines causing radiologists to become obsolete is fallacious, if not laughable. Radiology is among the fastest-growing fields in the last decade, and the number of radiologists has been steadily increasing over that time. Despite this increase in numbers, some countries are still short on radiologists, giving you an idea of how much demand there is for the profession.
Artificial intelligence will undoubtedly reshape how radiologists do their job, but it can never replace them. Dr. Curtis P. Langlotz, a professor at Stanford University’s radiology department, says that this mentality is a result of how people have oversimplified what radiologists do. One of the most common misconceptions about radiologists is that their work only involves analyzing images.
“A comprehensive catalog of radiology diagnoses lists nearly 20,000 terms for disorders and imaging observations and over 50,000 causal relations. Algorithms that can help diagnose common conditions are a major step forward, but an experienced radiologist is looking for numerous conditions all at once. Only some of these assessments can be performed with AI,” Langlotz explains.
Efficiency is one of the most important aspects of radiology. Fast and effective processing means people will have to wait for less to receive scans and the necessary treatment, which can save thousands of lives through early detection and medication. With the help of new AI technology, radiologists can be alerted to acute conditions in a timely manner, accelerating the time it takes to solve a particular case.
The impact of AI on radiology can best be compared to how autopilot technology affected commercial flights. The innovations on flight systems allowed repetitive and easy tasks such as safety checks and collision-avoidance systems to be fully automated, but the pilots were still there to take over manually when there’s an unforeseen glitch or malfunction in the system.
The same applies to AI technology in radiology. While the new systems will definitely make several detection tasks easier, the radiologist will still be the one to offer a qualified oversight over the diagnostic processes. As AI develops and learns more about the functions of various radiology duties, the radiologist can delegate more tasks to better focus on the patient’s needs.
AI should not be seen as a threat to radiologists. Instead, AI should be embraced and adapted so that patients can receive better quality care while strengthening the industry further.