![]() The GPT has been trained on large amounts of text to correlate words in context, for which it handles about 175 billion parameters. “ChatGPT is a computational natural language processing system built by OpenAI on top of a GPT3.5 (Generative Pretrained Transformer). ![]() ![]() Prof Alfonso Valencia, ICREA professor and director of Life Sciences at the Barcelona National Supercomputing Centre (BSC), said: The following comments are provided by our colleagues at SMC Spain: More generally this research underlines the need to base technology solutions on the full scope of the challenge, in this case providing comprehensive, in-person clinical care to patients from a wide range of populations.” “While ChatGPT continues to demonstrate an impressive ability to generate logical content in numerous settings, these results serve to highlight the limitations of written tests as the only way of assessing performance in complex and multi-disciplinary professions such as medicine. Prof Peter Bannister, Biomedical Engineer & Executive Chair, Institution of Engineering and Technology (IET), said: This human superiority won’t last forever, though one day, AIs will be better than us at almost every task.” One caveat, though, is that the US Medical Licensing Exam is designed to be hard for humans, not for machines there are many areas where humans are much more effective than AIs (such as moving about in cluttered spaces or interpreting social cues). “This is an impressive performance, and we should expect to see more such successes in AI in the future. I can imagine tools such as this one, summarizing information and answering questions, not actually practicing medicine.”ĭr Stuart Armstrong, Co-Founder and Chief Researcher at Aligned AI, said: “More importantly for me as a scientist: this approach can greatly help us to develop better ways for researchers to process large amounts of literature. “Still, it is part of an exciting series of new developments in AI. It can also be useful for training students. ![]() On the other hand, once this is refined to the point of actually passing an exam, we may want to reconsider how we assess new doctors. “On the one hand we are in the presence of a statistical mechanism trained to generate text (new but ‘similar’ to the one it was trained upon), in the right context and way, so we should not talk about understanding, or related concepts. The way the assessment was done, one could improve it by introducing more “blindness” in the adjudicators, for example mixing GPT answers to human answers, in an anonymized setting, but this does not seem to have been done.” “Care was taken to ensure that the test questions were not part of the training set. “This does not remotely suggest that chatGPT has any comparable knowledge to a human, since the test might be a good predictor of performance ONLY for those who have already a MD and done a residency, that is for a very pre-selected population. “The software chatGPT achieved an accuracy “close to” (which means short of) the passing accuracy in most settings, but it was close, and within the passing range for some tasks (see Figure 2a in the paper). The minimum passing accuracy is 60% (and the pass rate seems to be well above 90% ).” In the US, Physicians with a Doctor of Medicine (MD) degree are required to pass the USMLE for medical licensure. “The article describes how chatGPT was applied to generate answers to a 3-part test called USMLE. Prof Nello Cristianini, Professor of Artificial Intelligence at the University of Bath, said: Expert reaction to study on ChatGPT almost passing the US Medical Licensing ExamĪ study published in PLOS Digital Health looks at the performance of ChatGPT on US Medical Licensing Exam (USMLE).
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