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BACKGROUND: The rapid progression of artificial intelligence (AI) and large language models (LLMs), such as ChatGPT, has contributed to increase its utility and popularity in various fields. Discourse about AI's potential role in different aspects of scientific literature such as writing, data analysis, and literature review, is growing as the programs continue to improve their capabilities. This study utilizes a recently released ChatGPT tool that allows users to create customized GPTs to highlight the potential of customizable GPTs tailored to prepare and write research manuscripts. METHODS: We developed our 2 GPTs, Neurosurgical Research Paper Writer and Medi Research Assistant, through iterative refinement of ChatGPT 4.0's tool, GPT Builder. This process included providing specific and thorough instructions along with repetitive testing and feedback-driven adjustments to finalize a version of the model that fit our needs. RESULTS: The GPT models that we created were able to efficiently and consistently produce accurate outputs from inputted prompts based on their specific configurations. It effectively analyzed existing literature that it found and synthesized information in ways that were reliable and written in ways comparable to manuscripts authored by scientific professionals. CONCLUSIONS: While the ability of modern AI to generate scientific manuscripts has shown significant progress, the persistence of fallacies and miscalculations suggest that the development of GPTs requires extensive calibration before achieving greater reliability and consistency. Nevertheless, the prospective horizon of AI-driven research holds promise in streamlining the publication workflow and increasing accessibility to novel research.
Kabir et al. (Tue,) studied this question.