Maternal Medical Information Extraction (MaMIE) System

نویسندگان

  • Allan Borra
  • Karla Delos Santos
  • Daniel Gonzales
  • Alden Reyes
چکیده

This paper discusses the development of an information extraction system for maternal health records. Current investigated maternal health records that exist in hospitals are written in a long and detailed paragraphs in text documents. Information extraction processes unstructured, natural language text, such as maternal health records, to extract useful information from the text. MaMIE (Maternal Medical Information Extraction) System is designed to extract information from medical narratives obtained from De La Salle University Medical Center (DLSUMC) in Dasmarinas, Cavite. MaMIE System is composed of seven modules namely Text Zoner, Sentence Splitter, POS Tagger, Named-Entity Recognizer, Preparser, Coreferencer and Semantic Interpreter. An Obstetric Gynecologist from DLSUMC defined the fields of the template. The system was tested over 12 documents with the results of 87.39% Precision, 86.74% Recall and 87.06% Fmeasure.

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تاریخ انتشار 2013