迈向自动药物警戒:分析患者对肿瘤药物的评价和看法

Arpita Mishra, A. Malviya, Sanchit Aggarwal
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引用次数: 20

摘要

药品的副作用、不良反应、警告、注意事项等信息的收集、检测和监测是一项具有挑战性的任务。随着用户论坛的出现,在线评论已经成为产品信息的重要来源。在这项工作中,我们的目标是利用不同健康社区患者的药物评论来识别经常发生的问题。我们将这些问题与食品和药物管理局(FDA)批准的药物标签进行比较,以寻求可能的改进。我们专注于肿瘤药物,并开发了一个可扩展的系统,用于针对患者评论的适应症和各自症状的干预制图。使用这些映射,我们的系统能够比较FDA标签的不同部分以获得建议。我们使用基于支持向量机的框架进行情感分析,对药物进行整体评级。我们进一步结合基于方面的情感分析来寻找针对特定目标的药物审查方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Automatic Pharmacovigilance: Analysing Patient Reviews and Sentiment on Oncological Drugs
The collection, detection and monitoring of information such as side effects, adverse effects, warnings, precautions of pharmaceutical products is a challenging task. With the advent of user forums, online reviews have become a significant source of information about products. In this work, we aim to utilize pharmaceutical drugs reviews by patients on various health communities to identify frequently occurring issues. We compare these issues with food and drug administration (FDA) approved drug labels for possible improvements. We focus on Oncological drugs and develop a scalable system for mapping of interventions against indication and the respective symptoms from patient comments. Using these mappings, our system is able to compare different sections of FDA labels for recommendations. We use SVM based framework for sentiment analysis to give an overall rating to the drugs. We further incorporate aspect based sentiment analysis for finding the orientation of drug reviews for specific targets.
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