Core Insights - The study demonstrates that large language models (LLMs) can significantly assist physicians in overcoming technical barriers in medical AI research, with project completion rates increasing from 25% to 87% when using LLMs [11][12] - Despite the benefits, the research highlights potential risks associated with LLMs, including the possibility of dependency and the phenomenon of "hallucination" where AI may generate incorrect information [8][12] Study Overview - The research titled "The effectiveness of large language models in medical AI research for physicians: A randomized controlled trial" was published on November 26, 2025, in Cell Reports Medicine [4] - Conducted by a team from Sun Yat-sen University, the study involved a randomized controlled trial with 64 primary ophthalmologists, assessing the effectiveness of LLMs in an "automated cataract identification" project [6][7] Results - The intervention group using ChatGPT-3.5 had a total project completion rate of 87.5%, compared to 25.0% in the control group, and a non-assisted completion rate of 68.7% versus 3.1% [7] - After a washout period, 41.2% of successful intervention participants were able to complete new projects independently without LLM support [7] - Concerns were raised among participants, with 42.6% worried about mindlessly repeating AI-generated information and 40.4% fearing that AI could foster lazy thinking [7] Conclusion - The study concludes that while LLMs can democratize medical AI research and help physicians navigate technical challenges, the long-term risks associated with their use, such as dependency, require further investigation [8][12]

Core Insights - The article discusses the integration of interdisciplinary research in fields such as biology, chemistry, and computer science, highlighting its role in advancing digital medicine and healthcare services [2] - Despite the potential of technologies like artificial intelligence (AI) in biomedicine, their widespread application is hindered by technical barriers and limited expertise among physicians [2][5] - A recent study demonstrated that large language models (LLMs) can assist physicians in overcoming these technical challenges, although concerns about dependency and misinformation remain [3][6] Study Findings - A randomized controlled trial involving 64 primary ophthalmologists showed that the use of LLMs like ChatGPT-3.5 significantly improved project completion rates from 25% to 87.5% [5][7] - After a two-week washout period, 41.2% of successful intervention participants were able to complete new projects independently without LLM support [5][7] - The study identified potential risks associated with LLMs, including the tendency for physicians to rely on AI-generated information without full understanding [5][9] Implications - The findings suggest that LLMs can democratize medical AI research by helping physicians navigate design, execution, and reporting challenges [9] - However, the long-term risks of dependency on LLMs warrant further investigation to ensure safe and effective use in clinical settings [6][9]