Jianwei Leng

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Manually annotating clinical document corpora to generate reference standards for Natural Language Processing (NLP) systems or Machine Learning (ML) is a time-consuming and labor-intensive endeavor. Although a variety of open source annotation tools currently exist, there is a clear opportunity to develop new tools and assess functionalities that introduce(More)
The Health Insurance Portability and Accountability Act (HIPAA) Safe Harbor method requires removal of 18 types of protected health information (PHI) from clinical documents to be considered "de-identified" prior to use for research purposes. Human review of PHI elements from a large corpus of clinical documents can be tedious and error-prone. Indeed,(More)
BACKGROUND The ShARe/CLEF eHealth challenge lab aims to stimulate development of natural language processing and information retrieval technologies to aid patients in understanding their clinical reports. In clinical text, acronyms and abbreviations, also referenced as short forms, can be difficult for patients to understand. For one of three shared tasks(More)
INTRODUCTION/OBJECTIVE Pulmonary function tests (PFTs) are objective estimates of lung function, but are not reliably stored within the Veteran Health Affairs data systems as structured data. The aim of this study was to validate the natural language processing (NLP) tool we developed-which extracts spirometric values and responses to bronchodilator(More)
Application of virtual reality is a promising technology that combines the virtual reality approach to advanced modeling, simulation and user interface techniques [1]. Power electronics is a vital subject in the electric engineering, and furthermore, hands-on experiment is an important component in the subject. In the experiment, students cannot see the(More)
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