Robots, radiologists, and results

Abstract

AI may facilitate workflows, but human input is still crucial

Large language models (LLM) and ChatGPT: what will the impact on nuclear medicine be?

“…Only with special dispensation was it capable of passing only two of ten mock examinations and it ranked last alongside its 26 human peers [14]. In contrast, ChatGPT was capable of passing or being close to passing all three parts of the United States Medical Licensing Exam (USMLE) without additional training or prompts [1] and a Chinese AI tool Xiaoyi (meaning "little doctor") was, with training, capable of passing the Chinese Medical Licensing Exam [15]. Readers of this letter will doubtless be familiar with the hyperbole surrounding the role of AI in diagnostic radiology and nuclear medicine, exemplified by Hinton's famous and now controversial statement in 2013 that "we stop training radiologists now" [16].…”

Crumbs of comfort in this time of despair

“…Comfort is also found in the solidarity and camaraderie of hardworking and dedicated colleagues, for whom artificial intelligence is surely no substitute (doi:10.1136/bmj-2022-072826, doi:10.1136/bmj.o2853). 34 We highlight unsung heroes whose efforts historically go unnoticed despite their invaluable contribution to patient care (doi:10.1136/bmj.o2842, doi:10.1136/bmj.o2774). 56 Not only should these colleagues be seen but they deserve to be fully recognised (doi:10.1136/bmj.o3017).…”