PhD Dissertation Proposal
“S:PT.-HAS NO PMD.”
Information Extraction from Clinical Notes
Clare Grasso
11:00am Monday, 4 August 2014, ITE 325b
Information Extraction from Clinical Notes
Clinical decision support (CDS) systems aid clinical decision making by matching an individual patient’s data to a computerized knowledge base in order to present clinicians with patient-specific recommendations. The need for methods to extract the clinical information in the free-text portions of the clinical record into a form that clinical decision support systems could access and utilize has been identified as one of the top five grand challenges in clinical decision support. This research focuses on investigating scalable machine learning and semantic techniques that do not rely on an underlying grammar to extract medical concepts in the text in order to apply them in CDS on commodity hardware and software systems. Additionally, by packaging the extracted data within a semantic representation, the facts can be combined with other semantically encoded facts and reasoned over. This allows other clinically relevant facts to be inferred which are not directly mentioned in the text and presented to the clinician for decision making.
Committee: Drs. Anupam Joshi (chair), Tim Finin, Aryya Gangopadhyay, Charles Nicholas, Claudia Pearce and Eliot Siegel