03/30/2022
By Ian Chen

Computer Science Colloquium

Title: Automatic Information Retrieval and Extraction from Electronic Health Records

Location: Via Zoom https://uml.zoom.us/j/7311268370 (Passcode: cstalks)
Time: Friday, April 1, 2022, 3:30-4:30 p.m.

Abstract: Healthcare systems are changing in the era of big data. Advances of artificial intelligence in healthcare make it possible for healthcare providers to sift through tremendous amounts of information efficiently, which eventually help them take care of their patients better. There are various types of health information ranging from medical literature to pathology reports. My research goal is to develop machine learning methods that can efficiently utilize Electronic Health Records (EHR), which contain medical and treatment history of patients, to facilitate decision making of physicians in their clinical practice. In this talk, I will first introduce our work about question answering on EHR, including text-to-SQL query generation and clinical knowledge base question answering, which aims to seek answers for clinical activity related questions from Tabular EHR and unstructured clinical notes, respectively. This work helps us understand more about the challenges in retrieving information from different data types in EHR. Finally, I will introduce our current work about event extraction from unstructured texts.

Bio: Ping Wang is an Assistant Professor in the Department of Computer Science at Stevens Institute of Technology. She received her Ph.D. from Virginia Tech under the supervision of Dr. Chandan K. Reddy in 2021. Her research interests are in the broad area of data mining and machine learning with particular focus on healthcare analytics, including clinical question answering, information extraction, graph mining, and survival analysis. She has published papers in leading conferences (e.g., WWW, CIKM, and AAAI) and high impact journals (e.g., ACM Computing Surveys and IEEE TKDE). She won the “Research PhD Student of the Year” award (one per year) from the Department of Computer Science at Virginia Tech in 2021.

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