Welcome to our next IS-seminar:
Making Natural Language Processing (NLP) More Accessible for Analysis of Clinical Text with Dr. Wendy Chapman from University of California, San Diego.
When: Wednesday June 8th 12.00-13.00
Where: 6405A Forum 100 DSV/Stockholm University, Kista
Abstract
In spite of decades of research in NLP, applications for clinical text have not yet had muchof an impact. Researchers in clinical NLP are working towards making NLP more accessible through common data models, shared datasets, and web services. I will illustrate NLP’spotential application to clinical text with two applications we have developed, will describe initiatives leading to more collaborative development, and will summarize the vision for an NLP ecosystem that was shaped during a recent UCSD workshop. The goal of the ecosystem is toprovide an environment for easier development, application, and benchmarking of clinical NLP tools.
Wendy Chapman’s Bio
After studying linguistics, Dr. Wendy Chapman received her Ph.D in Medical Informatics at theUniversity of Utah with a research focus of natural language processing (NLP). After ten years at the University of Pittsburgh, Dr. Chapman joined UCSD. Her work has mainly addressed extraction of information from clinical reports, including identifying evidence of acute bacterial pneumonia from chestradiography reports and evidence of conditions relevant to detecting disease outbreaks from emergency department reports. She leads the American Medical Informatics Association NLP Working Group and several efforts to develop a collaborative infrastructure for developmentand application of NLP.