Exploring the use cases and limitations of large language models in the biomedical and clinical tasks

Abstract The development of large language models (LLMs) in recent years has shown several opportunities for improving the medical sector and processing unstructured electronic medical records. Despite the potential of these models, their application in the biomedical and clinical fields needs to comply with regulations and mitigate existing biases, nonfactual information generation, and any potential privacy concerns. Successful implementations of LLMs need an understanding of their use cases and limitations for strategies to revolutionize the healthcare industry and operations. This research does an exhaustive assessment of the published biomedical and clinical language models to comprehend the current problems, explore the best methods for overcoming the constraints and get the models suitable for use in regulated conditions.