A significant portion of data in the healthcare industry exists as narrative text, such as clinical notes in electronic health record (EHR) systems, clinical trial descriptions, biomedical literature, and consumer-generated content on social media and online forums. With the advancements in Natural Language Processing (NLP) and Artificial Intelligence (AI) techniques, valuable insights, such as symptoms and causal relationships between medical concepts, can be extracted from various text data to aid in clinical decision-making and improve healthcare outcomes.
This presentation will discuss recent work in applying NLP and AI techniques to extract clinical concepts from clinical notes and combine them with structured data for analyzing patient outcomes. It will also delve into how NLP and AI can be used to analyze and retrieve biomedical literature, extract information from healthcare guidelines, and develop guided keyphrase extractions from text. Finally, the presentation will touch upon the challenges and issues that need to be addressed, as well as future opportunities for innovative research.
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