Presented by: Laurence Hou MD
Hackensack University Medical Center

Introduction

The creation and editing of scientific abstracts are critical for succinctly summarizing research studies. This study explores the use of ChatGPT, an artificial intelligence (AI) language model, to enhance abstract optimization by improving conciseness, adhering to word count limitations, and providing additional value-add features. The objective is to evaluate the effectiveness of ChatGPT in abstract optimization for abstracts to be submitted to the World Congress of Endourology.

Materials

We conducted a study of six diverse minimally invasive urologic surgery scientific abstracts. ChatGPT was employed as an intelligent assistant in two main stages: initial generation and iterative refinement. The model was used to draft preliminary abstracts based on research materials and key findings. The iterative refinement process involved interactive fine-tuning of abstracts using ChatGPT's real-time feedback and suggestions. 

Results

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ChatGPT facilitated concise expression and adherence to word count restrictions by providing estimated word counts for each section. The iterative refinement process helped remove redundancies and extraneous details, optimizing abstracts for brevity. ChatGPT's language proficiency also enhanced the overall quality of the abstracts by suggesting improved vocabulary choices, refining sentence construction, and ensuring consistency of terminology.

 

Conclusion

ChatGPT proved highly useful in abstract optimization for the World Congress of Endourology, enhancing readability, quality, and time efficiency. Researchers can leverage ChatGPT to achieve concise, impactful abstracts.  It is important to note that human oversight is necessary to evaluate and validate the generated suggestions for scientific accuracy and context appropriateness. The integration of AI language models holds significant promise for efficient communication of research findings.

Funding

N/A

Co-Authors

Yu Zhang, MD
Hackensack University Medical Center

Ernest Tong, MD
Hackensack University Medical Center

Ravi Munver, MD, FACS
Hackensack Unviersity Medical Center