Title

Session 5 - Natural Language Processing: A Simple Introduction to Natural Language Processing and Its Clinical Applications in the Era of Artificial Intelligence

Presenter Information/ Coauthors Information

Yanshan Wang, Mayo Clinic

Presentation Type

Invited

Track

Other

Abstract

With the rapid adoption of electronic health records (EHRs), it is desirable to harvest information and knowledge from EHRs to support automated systems at the point of care and to enable secondary use of EHRs for clinical and translational research. Following the Health Information Technology for Economic and Clinical Health Act (HITECH Act) legislation in 2009, many health care institutions adopted EHRs, and the number of studies using EHRs has increased dramatically. However, much of the EHR data is in a free-text form. Compared to structured data, free text is a more natural and expressive method to document clinical events and facilitate communication among the care team in the health care environment. Natural language processing (NLP), a subfield of artificial intelligence (AI), has become a critical technique in automatically extracting and encoding clinical information from free text EHRs for clinical decision support, quality improvement, and clinical research. This talk will provide a simple introduction to NLP, along with some real-world clinical applications in the nation's top-ranked hospital, Mayo Clinic.

Start Date

2-11-2020 11:00 AM

End Date

2-11-2020 12:00 PM

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Feb 11th, 11:00 AM Feb 11th, 12:00 PM

Session 5 - Natural Language Processing: A Simple Introduction to Natural Language Processing and Its Clinical Applications in the Era of Artificial Intelligence

Dakota Room 250 A/C

With the rapid adoption of electronic health records (EHRs), it is desirable to harvest information and knowledge from EHRs to support automated systems at the point of care and to enable secondary use of EHRs for clinical and translational research. Following the Health Information Technology for Economic and Clinical Health Act (HITECH Act) legislation in 2009, many health care institutions adopted EHRs, and the number of studies using EHRs has increased dramatically. However, much of the EHR data is in a free-text form. Compared to structured data, free text is a more natural and expressive method to document clinical events and facilitate communication among the care team in the health care environment. Natural language processing (NLP), a subfield of artificial intelligence (AI), has become a critical technique in automatically extracting and encoding clinical information from free text EHRs for clinical decision support, quality improvement, and clinical research. This talk will provide a simple introduction to NLP, along with some real-world clinical applications in the nation's top-ranked hospital, Mayo Clinic.