LLM dermatological patient handouts - supplementary data

Supplementary material for Assessment of Large Language Models to Generate Patient Handouts for the Dermatology Clinic: a single-blinded randomized study LLM handouts methods describes the overall analysis and outputs for the PEMAT and readability scores. LLM dermatological patient handouts.R is the code used for the statistical analysis. LLM_readability_scores, PEMAT, LLM_attending_rank, rater_df, and LLM_randomization_protocol are the raw data used for analysis. Supplementary Figures 1-3: Readable versions of the data presented in graphical format for easier understanding. Supplementary Tables 1-3: ChatGPT handouts, Bard handouts, and BingAI handouts are the respective handouts and prompts generated for this study. Supplementary Table 4: A table showcasing side-by-side examples of the differences in LLM outputs. CONSORT AI checklist: CONSORT AI checklist for this study.《评估大语言模型（Large Language Model，LLM）生成皮肤科门诊患者宣教手册的单盲随机研究》补充材料 本研究的大语言模型宣教手册方法章节阐述了针对患者教育材料评估工具（Patient Education Materials Assessment Tool，PEMAT）与可读性评分的整体分析流程及输出结果。LLM_dermatological_patient_handouts.R 为本次统计分析所用的代码文件。LLM_readability_scores、PEMAT、LLM_attending_rank、rater_df 与 LLM_randomization_protocol 为本次分析所用的原始数据集。 补充图1至3：以可视化图形格式呈现的易懂数据版本，便于读者理解。 补充表1至3：ChatGPT宣教手册、Bard宣教手册与BingAI宣教手册，即为本研究分别生成的对应宣教手册及提示词。 补充表4：展示大语言模型输出差异的对照示例表格。 CONSORT AI检查表：本研究所用的CONSORT AI检查表。