TL;DR:
- The Brown Neurosurgery Department recently published two preprints evaluating the performance of AI Large Language Models (ChatGPT, GPT-4, and Google Bard) in the neurosurgery written board exams and oral board preparatory question bank.
- The results of these studies showed that the AI models performed exceptionally well in both exams, with GPT-4 outperforming the other models.
- The study was inspired by two neurosurgery residents who were studying for their board exams and saw ChatGPT pass other standardized exams.
- Although the results are exciting, the AI models still have limitations, such as being unable to see images and potentially asserting false information.
- There are also important ethical considerations, such as the potential for these models to propagate health disparities and provide misleading information in real-world scenarios.
- The experts agree that the integration of AI into medicine holds great promise but must be approached thoughtfully and with a focus on testing and addressing limitations.
- The future of AI in medicine is expected to evolve, with AI serving as assistants to medical providers and helping with patient documentation and communication.
Main AI News:
The Brown Neurosurgery Department has recently published two groundbreaking preprints that assess the performance of Artificial Intelligence Large Language Models ChatGPT, GPT-4, and Google Bard in the field of neurosurgery. The results of these studies have attracted widespread attention, as they demonstrate the potential of AI models to revolutionize the healthcare industry.
The preprints compare the performance of these AI models in both written and oral board exams, which are crucial evaluations for neurosurgeons. The written exams assess a candidate’s knowledge of basic neurosurgery principles, while the oral exams challenge the candidate’s higher-order thinking and clinical experience. The results of these preprints show that the AI models performed exceptionally well in both exams, with GPT-4 surpassing the other models with a score of 82.6% in higher-order case management scenarios.
The inspiration for this study came from fifth-year Neurosurgery Resident Rohaid Ali, who was studying for his board exam with his close friend Ian Connolly, another neurosurgery resident. They were amazed to see that ChatGPT was able to pass other standardized exams and wondered if it could answer any questions on their exam. This prompted Ali, Connolly, and Oliver Tang to conduct these studies and explore the potential of AI in the field of neurosurgery.
While these results are certainly exciting, it’s important to note that the AI models still have limitations that must be addressed. For example, as text-based models, they are unable to see images and score significantly lower in imaging-related questions that require higher-order reasoning. They also have the potential to assert false information, referred to as “hallucinations,” in their answers.
Rohaid Ali, one of the co-first authors of the study, emphasized the need to safely integrate AI models into patient care while actively investigating their limitations. In real clinical scenarios, neurosurgeons may receive misleading or irrelevant information from these models, and it’s crucial to understand their limitations to ensure the best possible outcome for patients.
The integration of AI into the medical field offers significant potential but also poses significant ethical dilemmas. Rohaid Ali, a co-lead author of the study, highlighted instances where the AI model’s correct responses to certain scenarios were unexpected. For instance, when posed with a question about a serious gunshot injury to the head, the AI model determined that there was likely no surgical intervention that could significantly impact the course of the disease. This raises ethical questions about the use of AI models in providing medical recommendations.
Another concern is the potential for these models to propagate health disparities due to the biases inherent in the data they are trained on. Wael Asaad, associate professor of neurosurgery and neuroscience at Warren Alpert, stressed the importance of understanding and addressing these biases to prevent harmful recommendations. Albert Telfeian, Warren Alpert’s Professor of Neurosurgery, also highlighted the importance of human connections between doctors and patients that AI models still lack.
Looking to the future, Asaad predicts that the role of AI in medicine will evolve, with AI serving as an assistant to medical providers. He notes that AI models could help providers keep up with rapidly advancing medical knowledge and provide relevant resources and ideas for evaluating cases. Curt Doberstein, professor of neurosurgery at Warren Alpert, also emphasizes the potential for AI to assist with patient documentation and communication, helping to alleviate provider burnout and promoting doctor-patient interactions.
Ziya Gokaslan, professor and chair of neurosurgery at the Warren Alpert Medical School, recognizes the potential of AI in medicine and surgery but cautions that these systems must be tested effectively and used thoughtfully. All of the experts agree that the integration of AI into medicine is at the beginning stages and will require constant adaptation and learning as new technology and advancements emerge. Nevertheless, the potential for AI to transform the healthcare industry is exciting.
Conlcusion:
The recent findings from the Brown Neurosurgery Department demonstrate the potential of Artificial Intelligence Large Language Models in revolutionizing the healthcare industry. The ability of these models to perform exceptionally well in both written and oral neurosurgery board exams shows their potential to transform the way healthcare providers evaluate and treat patients.
However, it’s important to note that these models still have limitations that must be addressed and that there are important ethical considerations that must be taken into account. The integration of AI into medicine is at its early stages and will require constant adaptation and learning as new technology and advancements emerge.
For the market, this means that there is a growing demand for AI solutions in healthcare. Companies specializing in AI and healthcare technology will likely see increased investment and growth opportunities in this field. At the same time, it’s important for companies to approach the integration of AI into medicine thoughtfully and with a focus on addressing limitations and ethical considerations.
