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Text Mining and Natural Language Processing for Health Informatics: Recent Trends and the Way Forward
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.
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