Sentiments in Oncology: A Cancer treatment sentiment dataset

The Cancer Treatment Sentiment Dataset was compiled by collecting 14,419 patient comments from various multilingual websites in English, French, and German. Sources include popular platforms like Reddit, Drugs.com, AskPatient, and WebMD (English); Carenity and Espoir de Vie Cancer du Sein (French); and Medzin Forum Medecine (German). The dataset focuses on patient comments and experiences with three specific cancer treatments: Afinitor, Aromasin, and Folfox, and covers a timeframe from 2005 to 2024. This dataset has numerous potential applications. It can be used to develop machine learning models for classifying patient sentiments, identifying trends, and exploring common themes in patient feedback on cancer treatments. Healthcare professionals can leverage this data to gain deeper insights into patient concerns and preferences, enhancing patient care and support. Additionally, pharmaceutical companies can utilize this resource to gather real-world feedback on treatments, helping to inform drug development and improve patient outcomes.

该癌症治疗方案情感数据集由14,419份来自多种多语言网站（包括英语、法语和德语）的患者评论汇编而成。数据来源包括Reddit、Drugs.com、AskPatient和WebMD（英语）；Carenity和Espoir de Vie Cancer du Sein（法语）；以及Medzin Forum Medecine（德语）。本数据集聚焦于针对三种特定癌症治疗方案（Afinitor、Aromasin和Folfox）的患者评论与体验，时间跨度涵盖2005年至2024年。该数据集具有广泛的应用前景。可用于开发机器学习模型，以对患者的情感进行分类、识别趋势并探索患者对癌症治疗的反馈中的常见主题。医疗专业人员可利用这些数据，以深入洞察患者的关切与偏好，从而提升患者护理与支持的质量。此外，制药公司亦可利用此资源收集关于治疗的实际反馈，有助于指导药物研发并优化患者治疗效果。