Opportunities and Challenges for Incorporating Artificial Intelligence and Natural Language Processing in Neurology Education

Abstract

Since the launch of OpenAI's ChatGPT, the application of artificial intelligence (AI) in medical education has ignited a polarized discussion.Two main advancements will change the way we study and practice medicine, large language models (LLMs), such as generated pretrained transformer 4 (GPT-4), and natural language processing (NLP).While LLM performs language-related tasks, NLP enables machines to understand and generate human language.LLM and NLP allow neurology learners to access and synthesize information, albeit with some considerations.Medical learners struggle with an exponentially expanding medical knowledge, doubling every 73 days. 1 Internships are "training in the art of culling data." 2 Neurology's complexity, compounded by "neurophobia," underlines the need for efficacious knowledge acquisition and clinical application. 3wever, concerns arise regarding the trustworthiness of NLP-generated information.ChatGPT, for example, uses multiple sources of data sets obtained from the internet, such as Wikipedia and Reddit, wth early versions limited to knowledge up to 2021.NLP is programmed not to lie, yet these programs are known to "confabulate" and "hallucinate" to answer prompts.Learners and educators should know that NLP culls from a data set, bases recommendations from these input sources, and avoids biased decision making, but does not display inherent bias that exists in the data.AI assistance should be used carefully to protect patients' information.DocsGPT is one of the first Health Insurance Portability and Accountability Act (HIPAA)compliant AI assistance that is freely available through Doximity.On the positive side, imagine an NLP with access to all medical journals, summarizing the latest research on specific topics in minutes using the preferred medium, that is, written, audio, or video.Newer NLP tools, such as those created by John Snow Labs, are already capable of summarizing medical records and providing efficient data.NLP can also provide accurate data summarization of referral notes, charts, or laboratory results.It can write documentation, send result letters, and respond to insurance company requests.This enhances efficiency and allows neurologists and trainees to spend time with patients or in learning.The responses generated by ChatGPT are nearly indistinguishable from those provided by physicians. 4 The US Food and Drug Administration has approved 14 AI technologies for clinical neurologic applications.

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