Text Mining and Natural Language Processing for Health Informatics

V. Anoop
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Abstract

Health informatics deals with applying informatics to medicine and healthcare that aims to store, process, and retrieve large amounts of healthcare data to enable optimal collaboration between different stakeholders. This has several applications in the healthcare domain from extracting information from medical documents such as case reports and prescriptions to analyzing data from sensors available in wearable devices. Recent advancements in information and communication technologies fueled the need of devising intelligent technologies for analyzing such data – not only in various forms but also in large quantities. This has posed many challenges and opportunities to use techniques such as text mining, natural language processing (NLP), and deep learning to unearth the latent themes from the vast array of textual data. This chapter proposes some prominent works in health informatics that use text mining and NLP and also discusses some active research areas in these dimensions. This chapter will be useful to understand the recent advancements and future research dimensions.
健康信息学的文本挖掘和自然语言处理
健康信息学处理将信息学应用于医学和医疗保健,旨在存储、处理和检索大量医疗保健数据,以实现不同利益相关者之间的最佳协作。这在医疗保健领域有多种应用,从从病例报告和处方等医疗文档中提取信息到分析可穿戴设备中可用传感器的数据。最近信息和通信技术的进步促使人们需要设计智能技术来分析这些数据——不仅以各种形式,而且要大量分析。这给使用文本挖掘、自然语言处理(NLP)和深度学习等技术从大量文本数据中挖掘潜在主题带来了许多挑战和机遇。本章提出了健康信息学中使用文本挖掘和自然语言处理的一些突出工作,并讨论了这些方面的一些活跃研究领域。本章将有助于了解最近的进展和未来的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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