ChatGPT-4: AI Outperforms Humans in Psychiatry and Neurology Boards – Medriva
Artificial intelligence continues to revolutionize various sectors, and healthcare is not exempt. A recent study has found that ChatGPT-4, a large language model developed by OpenAI, has outperformed humans on a mock version of the American Board of Psychiatry and Neurology (ABPN) boards. The AI answered 85% of questions correctly, surpassing the human score of 73.8%. This has sparked a conversation on the potential role of AI in clinical medicine and education, along with the inherent risks and limitations.
In the study, ChatGPT-4 was subjected to a question bank approved by the ABPN. The AI showed remarkable performance in the behavioral, cognitive, and psychological categories, significantly outperforming humans. However, it had less success with epilepsy and seizures or neuromuscular topics. The researchers noted that while this accomplishment is impressive, it does not imply that the software possesses the ability to practice clinical medicine or replace human clinical decision-making.
Despite ChatGPT-4’s performance, the study highlighted the limitations and risks of relying on large language models for medical knowledge. While it answered the majority of questions correctly, its error rate was still high. Furthermore, the AI exhibited a tendency to express certainty even when it provided incorrect answers. This presents a significant risk in clinical settings, where incorrect information could lead to severe consequences.
The research emphasized the importance of human validation and fact-checking when using transformer technology in clinical or educational settings. Despite the AI’s ability to process and present large amounts of information, the accuracy of this information cannot be guaranteed. Hence, it is crucial to have a human in the loop to validate the AI’s outputs.
ChatGPT-4’s performance on the ABPN mock examination suggests that AI could have significant applications in medical education. With further refinements, large language models could be used to aid in teaching and learning in the medical field. For instance, a study aimed to analyze the pathology knowledge of ChatGPT-4 found that the AI could be a valuable resource in pathology education if trained on a larger specialized medical data set.
There are also indications that AI could be useful in specialized medical fields. A study found that ChatGPT might be a reliable resource for healthcare professionals in the context of inflammatory bowel disease (IBD). The AI showed the strongest reliability and usefulness in disease classification, diagnosis, activity, poor prognostic indicators, and complications when it sourced its responses from professional sources.
In conclusion, while AI, as exemplified by ChatGPT-4, shows promise in the medical field, it is essential to approach its application with caution. The technology’s limitations and potential risks should be thoroughly considered, and human validation remains a crucial step in the process.
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