Sentiments in Oncology: A Cancer treatment sentiment dataset

The Cancer Treatment Sentiment Dataset was compiled by collecting 14419 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.癌症治疗情感数据集（Cancer Treatment Sentiment Dataset）通过采集英、法、德三种语言的多平台患者评论共计14419条构建完成。其数据来源涵盖：英文平台红迪网（Reddit）、Drugs.com、AskPatient及WebMD；法语平台Carenity与Espoir de Vie Cancer du Sein；德语平台Medzin Forum Medecine。本数据集聚焦于三款特定癌症治疗方案——Afinitor、Aromasin与Folfox的患者评论及治疗体验，时间跨度为2005年至2024年。本数据集具备多项潜在应用价值：可用于开发机器学习模型，以实现患者情感分类、趋势识别及癌症治疗患者反馈中的共性主题挖掘；医疗从业人员可借助该数据集深入洞悉患者的顾虑与偏好，进而优化患者护理与支持服务；此外，制药企业可利用该资源收集治疗方案的真实世界反馈，为药物研发提供决策参考并改善患者临床结局。