Can AI save us from the arduous and time-consuming task of academic research collection? An international team of researchers led by Professor Masaru Enomoto of the Graduate School of Medicine at Osaka Metropolitan University sought to answer this question by investigating the credibility and efficiency of generative AI in the medical field.
In their study, the research team fed identical clinical questions and literature selection criteria to two generative AIs: ChatGPT and Elicit. The results were surprising. While ChatGPT suggested fictitious articles, Elicit proved to be efficient, offering multiple references within minutes and matching the accuracy of the human researchers.
Dr. Enomoto cautioned that while generative AI shows promise, it is still in its early stages. He explained, Access to information using generative AI is still in its infancy, so we need to exercise caution as the current information is not accurate or up-to-date. However, ChatGPT and other generative AIs are constantly evolving and are expected to revolutionize the field of medical research in the future.
The team’s findings on the comparison between ChatGPT and Elicit have been published in Hepatology Communications.
As the use of AI in various fields continues to grow, this study sheds light on its potential applications in medical research. With the ability to quickly sift through vast amounts of literature and offer relevant references, AI systems like Elicit could greatly enhance the efficiency of academic research. However, the research also underscores the need for caution and further development to ensure the accuracy and reliability of the information provided by generative AI.
The implications of this study are significant for researchers and practitioners in the medical field. The ability to access relevant literature efficiently can save time and resources, allowing for more effective decision-making and the advancement of medical knowledge. As generative AI continues to advance, it holds the promise of transforming the way medical research is conducted.
While the results of this study are encouraging, it is important to approach generative AI with a critical mindset. The current limitations of the technology, as demonstrated by the fictitious articles suggested by ChatGPT, highlight the importance of human oversight and verification. As AI systems evolve, researchers and developers must work hand in hand to ensure that they are accurate, reliable, and up-to-date.
As we enter an era where AI becomes increasingly intertwined with various aspects of our lives, it is crucial to explore its potential while being mindful of its limitations. The collaboration between humans and AI holds promise for the future of medical research, but it is essential to navigate this path with caution, ensuring that the information provided is accurate, trustworthy, and beneficial to society as a whole.
In conclusion, the study conducted by Professor Masaru Enomoto and his team exemplifies the ongoing efforts to harness the power of generative AI in the medical research field. While the comparison between ChatGPT and Elicit revealed the latter’s efficiency and accuracy, it is essential to exercise caution and recognize the limitations of current AI systems. With further advancements and regulatory measures, generative AI has the potential to revolutionize the way medical research is conducted, ultimately benefitting patients and healthcare professionals worldwide.
