In the world of academic research, the arduous and time-consuming task of collecting information has long been a challenge. However, a glimmer of hope emerges through the utilization of generative AI.
An international team of researchers recently delved into the credibility and efficiency of generative AI as a tool for gathering information, particularly in the field of medicine.
The study, spearheaded by Professor Masaru Enomoto from the Graduate School of Medicine at Osaka Metropolitan University, embarked on an intriguing experiment.
They presented identical clinical queries and literature selection criteria to two generative AI models: ChatGPT and Elicit. The outcome of their investigation has been published in Hepatology Communications.
The results of this investigation shed light on the capabilities of generative AI in the context of academic research. While ChatGPT presented fictitious articles as potential sources, Elicit emerged as an efficient contender.
Elicit demonstrated the ability to suggest multiple relevant references within mere minutes, matching the accuracy of human researchers.
Dr. Enomoto, reflecting on the motivation behind this research, explained, “Our inspiration for this study arose from the challenges of managing vast volumes of medical literature over extended periods.
It’s important to note that the current landscape of information accessibility through generative AI is in its early stages, and the accuracy and timeliness of the information it provides are not yet guaranteed.
Nevertheless, the potential of ChatGPT and other generative AIs is undeniable, and we anticipate that they will usher in a transformative era in the realm of medical research.”
In essence, this study serves as a glimpse into the future of academic research. While caution is warranted in relying solely on generative AI for information gathering due to current limitations, the ongoing evolution of these technologies promises a revolution in the field of medical research.
As these AI systems continue to improve and adapt, they hold the potential to streamline and enhance the way researchers access and utilize information, ultimately advancing the boundaries of knowledge and discovery in medicine and beyond.
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The research findings can be found in Hepatology Communications.
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