Training Program Title

Clinical Natural Language Processing, Some Tasks and Applications in Medicine

Contributor

Advance-CTR

CTSA Hub Administered

yes

Contact Information

Advance-CTR, AdvanceRI@Brown.edu

Training Program Description

In this talk, Professor Savova will position the latest developments in clinical Natural Language Processing (NLP) in the context of the explosive achievements in the broader NLP field. How can clinical NLP advance in the era of data hungry methods? Does it matter how the personally identifiable information is obliterated in clinical text? Prof. Savova will demonstrate how the latest methods are applied to core tasks – information extraction and temporal relation extraction – through some of the translational science initiatives in her lab (Deep Phenotyping for Oncology/DeepPhe, Temporal Histories of Your Medical Events/THYME).

Competency Keywords

Scientific writing, Biostatistics, Biomedical informatics, Data management, Research study management, Research process, Clinical research interactions, Documentation, Study design, Clinical trial, Clinical research, Biomedical research, Translational research

Digital Commons Disciplines

Biomedical Engineering and Bioengineering | Medical Education | Medicine and Health Sciences | Public Health | Translational Medical Research

Public

yes

Cost to Access

no

Competency Domains

Scientific Concepts and Research Design; Ethical and Participant Safety Considerations; Medicines Development and Regulation; Clinical Trials Operations; Study and Site Management; Data Management and Informatics

Learning Objectives

  • The latest developments in clinical Natural Language Processing (NLP) in the context of the explosive achievements in the broader NLP field.
  • How can clinical NLP advance in the era of data hungry methods?
  • Does it matter how the personally identifiable information is obliterated in clinical text?

Delivery Method

Online

Target Learners

Principal Investigators; Clinical Research Professionals (other than PI); MDs including residents, house officers, fellows, hospitalists; Post-doctoral scholars

Learning Level

Skilled

Onboarding

no

Frequency

Semi-Annually

Time Needed

60 minutes

Associated Assessment

no

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