- Country: TAIWAN
- Official Title: 副部主任
- Department: 長庚紀念醫院中醫內兒科
Speech Title
ChatGPT and Medical Research ChatGPT和醫學研究
Advanced large language models (LLM) like ChatGPT have revolutionized medical research by enabling sophisticated understanding and generation of human-like text. GPT-4’s enhanced reasoning, accuracy, and multimodal capabilities further expand medical applications. This presentation examines ChatGPT’s integration into medical research, highlighting benefits, limitations, and ethical considerations.
ChatGPT assists in literature reviews, hypothesis generation, patient data summarization, and decision support. It accelerates analysis of extensive medical literature, helping researchers stay current with new findings. Additionally, it enhances patient engagement by providing personalized health information and responding to queries, potentially improving health literacy and patient outcomes.
Despite its advancements, ChatGPT has limitations. The model may produce inaccurate or misleading information due to biases in training data or misinterpretation of complex medical concepts. GPT-4’s improved capabilities reduce but do not eliminate these issues. Its inability to verify facts or deeply understand context can lead to critical errors in medical settings.
Ethical considerations are crucial when integrating AI into healthcare, including concerns about patient privacy, data security, and the risk of dehumanizing care. Over-reliance on AI tools may lead to misuse, necessitating careful regulation and oversight. Transparency in AI operations, accountability for AI-generated content, and preserving human interaction are vital for ethical implementation.
This presentation provides a comprehensive overview of ChatGPT’s role in medical research, advocating a balanced approach that leverages its enhanced capabilities while addressing limitations and ethical challenges. By acknowledging these factors, we can responsibly optimize the use of advanced AI models like GPT-4 to advance medical research and improve patient care.