Introduction to Natural Language Processing in Health
Prerequisites: HIDS 401 Foundations of Health Informatics and HIDS 411 Clinical Data Science.
The objective of this course is to present a broad overview of methodologies to analyze and mine biomedical text automatically. Students will be exposed to some of the common and state-of-the-art software, algorithms and techniques to extract content and knowledge from biomedical texts. A particular emphasis will be placed on how these methodologies are used in the context of health care, clinical records and narratives, and how extracted information can be used to improve care.
Outcomes: Understand and apply artificial intelligence methodologies and software to automatically extract information from unstructured text; Assess and evaluate advantages and disadvantages of such methodologies; Understand and analyze how machine learning tools are used in a clinical context; Analyze how NLP techniques enrich structured data, improve accuracy of diagnosis, and their role in learning health systems.
The objective of this course is to present a broad overview of methodologies to analyze and mine biomedical text automatically. Students will be exposed to some of the common and state-of-the-art software, algorithms and techniques to extract content and knowledge from biomedical texts. A particular emphasis will be placed on how these methodologies are used in the context of health care, clinical records and narratives, and how extracted information can be used to improve care.
Outcomes: Understand and apply artificial intelligence methodologies and software to automatically extract information from unstructured text; Assess and evaluate advantages and disadvantages of such methodologies; Understand and analyze how machine learning tools are used in a clinical context; Analyze how NLP techniques enrich structured data, improve accuracy of diagnosis, and their role in learning health systems.