AI不会取代放射科医生，但将深刻改变其工作方式
AI won’t replace radiologists, but it will dramatically change their jobs
In 2016 Geoffrey Hinton, the Nobel-winning “godfather of AI,” predicted that radiologists—the physicians who read X-rays, ultrasounds, and other images to help make medical diagnoses—would find themselves replaced by computers within five years. Today the field can retort by quoting Mark Twain’s famous quip: The report of my death was an exaggeration.
2016年，诺贝尔奖得主、被誉为“人工智能教父”的杰弗里·辛顿预测，放射科医生——那些通过阅读X光片、超声波和其他影像来辅助医疗诊断的医生——将在五年内被计算机取代。如今，该领域可以用马克·吐温的名言来回应：关于我死亡的报道是夸大其词。
Radiology’s ranks are in fact growing steadily, with the number of practitioners expected to expand by 26 percent or more over the next three decades. But what Hinton may have missed about the dynamics of the job market should not obscure his prescience: He was correct that human physicians now have a silicon-based colleague in the room that matches or exceeds their performance. In fact, radiology is far and away medicine’s hot spot for AI, making it a bellwether for the adoption of expert decision-making systems across healthcare and perhaps in other fields.
事实上，放射科医生的队伍正在稳步增长，预计未来三十年内从业人数将增加26%或更多。但辛顿可能对就业市场动态的忽视不应掩盖他的先见之明：他正确指出，人类医生现在身边有一位硅基同事，其表现与人类相当甚至更优。实际上，放射学是医学领域中人工智能应用的热点，使其成为医疗保健乃至其他领域采用专家决策系统的风向标。
As of early 2026, about three-quarters of the 1,400 AI-enabled medical devices cleared by the Food and Drug Administration were for radiology. Some make physicians more efficient by drafting reports or alerting them to the images that urgently need attention. But other AI tools have the potential to improve on human performance by identifying abnormalities that may not be visible to the human eye, or interpreting images as well as—and sometimes better than—trained radiologists. For example, an analysis of 43 clinical trials concluded that AI-assisted colonoscopies reveal more polyps than conventional ones.
截至2026年初，美国食品药品监督管理局批准的1400种人工智能医疗设备中，约有四分之三用于放射学。有些设备通过起草报告或提醒医生注意急需关注的影像来提高效率。但其他人工智能工具有可能通过识别肉眼可能看不到的异常，或与训练有素的放射科医生一样好甚至有时更好的解读影像，来提升人类的表现。例如，一项对43项临床试验的分析得出结论，人工智能辅助的结肠镜检查比传统检查能发现更多的息肉。
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