自动化、自然语言处理、人工智能和机器学习在医院环境中识别和预防药物不良反应的作用

Akanksha Togra, S. Pawar
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引用次数: 1

摘要

患者安全是所有药物警戒活动的中心。由于多个协变量会影响药品对患者的安全性,因此需要大量数据来准确评估药品的安全性,从而评估药品的利益-风险平衡。自然语言处理、人工智能和机器学习被广泛用于促进制药行业的各种药物警戒活动。如果在医院环境中正确使用人工智能和机器学习,还可以促进从医院记录和出院摘要以及处方错误中识别不良事件,从而提醒治疗医生注意这一点。然而,需要在医院环境中充分探索使用这些技术的潜力,以促进安全数据的收集和评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Role of Automation, Natural Language Processing, Artificial Intelligence, and Machine Learning in hospital settings to identify and prevent Adverse Drug Reactions
Patient Safety is at the center of all pharmacovigilance activities. As several covariates can impact the safety of a medicinal product in patients, a large amount of data is required for an accurate assessment of the safety and therefore, the benefit-risk balance of a medicinal product. Natural language processing, Artificial Intelligence, and Machine Learning are being popularly used to facilitate various pharmacovigilance activities in the Pharma industry. Artificial Intelligence and Machine learning if properly used in hospital settings can also facilitate the identification of adverse events from hospital records and discharge summaries and prescription errors, thus, alerting treating physicians regarding the same. However, the potential of using these techniques needs to be fully explored in hospital settings to facilitate the collection and evaluation of safety data.
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