神经系统疾病的药物审查分析

Dipen Chawla, Disha Mohnani, Varsha Sawlani, Sujay Varma, Sujata Khedkar
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引用次数: 0

摘要

目前,由于医疗药物引起的不良反应是人类生命损失的主要原因之一。昂贵的实验室检测不足以获得大多数药物引起的所有不良反应。因此,在药物被批准使用后,开发对其效果进行监督的系统是当务之急。在这里,我们评估了一个自我操作系统,用于药物有效性识别的一组用户评论,这些评论是手动注释的。我们将尝试在已记录的药物不良反应与拟议系统获得的不良反应之间建立关系。为此,系统将使用未标记的数据。人们观察到,用户评论中包含了大量复杂的句子,这对自然语言构成了挑战。然而,这些用户评论也为进一步探索提供了巨大的空间。
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Drug review analytics of neurological disorders
These days, adverse reactions caused due to medical drugs are one of the major causes of loss of human life. Highly priced laboratory tests aren't enough to obtain all the adverse reactions caused by the majority of the drugs. As a result, it is the need of the hour to develop systems which would supervise effects of drugs after they are cleared for use. Here, we evaluate a self-operating system for drug effectiveness identification on a set of user comments which are annotated manually. We shall try to obtain a relation between the already documented adverse reactions of a drug and those obtained by the proposed system. For this purpose, the system would use unlabeled data. It has been observed that user comments contain a vast variety of complex sentences which pose a natural language challenge. However, these user reviews provide huge scope for further exploration as well.
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