Using GPT-3 to Build a Lexicon of Drugs of Abuse Synonyms for Social Media Pharmacovigilance.
Using GPT-3 to Build a Lexicon of Drugs of Abuse Synonyms for Social Media Pharmacovigilance.
复制标题
使用GPT-3来建造社交媒体药物措施的滥用同义词药物的词典。
DOI：
10.3390/biom13020387
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发表时间：
2023-02-18
期刊：
影响因子：
5.5
通讯作者：
中科院分区：
文献类型：
--
作者：
药物滥用在美国是一个严重的问题，2020年全国有超过9万例药物过量死亡。打击药物滥用的一个关键步骤是检测，监测和描述其随时间和地点的趋势，也称为药物警戒。虽然联邦报告系统在一定程度上实现了这一点，但它们通常具有高延迟和不完整的覆盖范围。基于社交媒体的药物警戒具有零延迟，易于访问和未经过滤，并受益于药物使用者愿意在线伪匿名分享他们的经验。然而，与高度结构化的官方数据源不同，社交媒体文本充斥着拼写错误和俚语，使得自动分析变得困难。生成式预训练Transformer 3（GPT-3）是一个大型自回归语言模型，专门用于少量学习，并在整个互联网的文本上进行训练。我们证明，GPT-3可以用来产生俚语和常见的拼写错误的滥用药物的条款。我们反复查询GPT-3，寻找滥用药物的同义词，并使用自动Google搜索和已知药物名称的交叉引用过滤生成的术语。当为阿普唑仑生成的术语被手动标记时，我们发现我们的方法产生了269个阿普唑仑的同义词，其中221个是未包含在社交媒体现有药物词典中的新发现。我们对98种滥用药物重复了这一过程，其中22种是广泛讨论的滥用药物，建立了一个口语化药物同义词词典，可用于社交媒体上的药物警戒。
Drug abuse is a serious problem in the United States, with over 90,000 drug overdose deaths nationally in 2020. A key step in combating drug abuse is detecting, monitoring, and characterizing its trends over time and location, also known as pharmacovigilance. While federal reporting systems accomplish this to a degree, they often have high latency and incomplete coverage. Social-media-based pharmacovigilance has zero latency, is easily accessible and unfiltered, and benefits from drug users being willing to share their experiences online pseudo-anonymously. However, unlike highly structured official data sources, social media text is rife with misspellings and slang, making automated analysis difficult. Generative Pretrained Transformer 3 (GPT-3) is a large autoregressive language model specialized for few-shot learning that was trained on text from the entire internet. We demonstrate that GPT-3 can be used to generate slang and common misspellings of terms for drugs of abuse. We repeatedly queried GPT-3 for synonyms of drugs of abuse and filtered the generated terms using automated Google searches and cross-references to known drug names. When generated terms for alprazolam were manually labeled, we found that our method produced 269 synonyms for alprazolam, 221 of which were new discoveries not included in an existing drug lexicon for social media. We repeated this process for 98 drugs of abuse, of which 22 are widely-discussed drugs of abuse, building a lexicon of colloquial drug synonyms that can be used for pharmacovigilance on social media.
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影响因子：
15.2
作者：
Korngiebel DM;Mooney SD
通讯作者：
Mooney SD
DOI：
10.3390/ph15060675
发表时间：
2022-05-27
期刊：
Pharmaceuticals (Basel, Switzerland)
影响因子：
--
作者：
通讯作者：
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药物不良事件的文本挖掘：前景、挑战和最新技术。
影响因子：
4.2
作者：
Harpaz, Rave;Callahan, Alison;Tamang, Suzanne;Low, Yen;Odgers, David;Finlayson, Sam;Jung, Kenneth;LePendu, Paea;Shah, Nigam H.
通讯作者：
Shah, Nigam H.
影响因子：
7.4
作者：
Lavertu A;Hamamsy T;Altman RB
通讯作者：
Altman RB
影响因子：
3
作者：
Eshleman R;Singh R
通讯作者：
Singh R