This paper discusses the effectiveness of leveraging Chatbot: Generative Pre-trained Transformer (ChatGPT) versions 3.5 and 4 for analyzing research papers for effective writing of scientific literature surveys. The study selected the \textit{Application of Artificial Intelligence in Breast Cancer Treatment} as the research topic. Research papers related to this topic were collected from three major publication databases Google Scholar, Pubmed, and Scopus. ChatGPT models were used to identify the category, scope, and relevant information from the research papers for automatic identification of relevant papers related to Breast Cancer Treatment (BCT), organization of papers according to scope, and identification of key information for survey paper writing. Evaluations performed using ground truth data annotated using subject experts reveal, that GPT-4 achieves 77.3\% accuracy in identifying the research paper categories and 50\% of the papers were correctly identified by GPT-4 for their scopes. Further, the results demonstrate that GPT-4 can generate reasons for its decisions with an average of 27\% new words, and 67\% of the reasons given by the model were completely agreeable to the subject experts.

使用ChatGPT 3.5和4对研究论文进行分析以提高科学文献调查的有效性，选择“人工智能在乳腺癌治疗中的应用”作为研究主题，使用ChatGPT模型自动识别相关论文、对论文按范围进行组织和确定调查论文的关键信息，结果显示GPT-4能以77.3%准确率识别研究论文类别，50%的论文的范围能被GPT-4正确识别，且67%的模型给出的原因是专家完全同意的。

AI洞察：利用ChatGPT智能进行研究论文分析的案例研究