Medical abstract inference dataset

• Main Author: De León, Eduardo Enrique
• Other Authors: Regina Barzilay.
• Format: Others
• Language: English
• Published: Massachusetts Institute of Technology 2018
• Subjects: Electrical Engineering and Computer Science.
• Online Access: http://hdl.handle.net/1721.1/119516

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017. === This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. === Cataloged from student-submitted PDF version of thesis. === Includes bibliographical references (page 35). === In this thesis, I built a dataset for predicting clinical outcomes from medical abstracts and their title. Medical Abstract Inference consists of 1,794 data points. Titles were filtered to include the abstract's reported medical intervention and clinical outcome. Data points were annotated with the interventions effect on the outcome. Resulting labels were one of the following: increased, decreased, or had no significant difference on the outcome. In addition, rationale sentences were marked, these sentences supply the necessary supporting evidence for the overall prediction. Preliminary modeling was also done to evaluate the corpus. Preliminary models included top performing Natural Language Inference models as well as Rationale based models and linear classifiers. === by Eduardo Enrique de León. === M. Eng.