research data . Dataset . 2019 . Embargo end date: 05 Sep 2018

Data from: Trends in anesthesiology research: a machine learning approach to theme discovery and summarization

Rusanov, Alexander; Miotto, Riccardo; Weng, Chunhua;
Open Access
  • Published: 01 Jan 2019
  • Publisher: Data Archiving and Networked Services (DANS)
Abstract
Objectives: Traditionally, summarization of research themes and trends within a given discipline was accomplished by manual review of scientific works in the field. However, with the ushering in of the age of “big data”, new methods for discovery of such information become necessary as traditional techniques become increasingly difficult to apply due to the exponential growth of document repositories. Our objectives are to develop a pipeline for unsupervised theme extraction and summarization of thematic trends in document repositories, and to test it by applying it to a specific domain. Methods: To that end, we detail a pipeline, which utilizes machine learning...
Subjects
free text keywords: Life sciences, medicine and health care, Life sciences, medicine and health care, Natural Language Processing, Data Visualization, Topic Modeling, Machine Learning, (:tba)
Funded by
NIH| Anesthesiology Research Training
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 2T32GM008464-21
  • Funding stream: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
,
NIH| Bridging the Semantic Gap Between Research Eligibility Criteria and Clinical Data
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01LM009886-02
  • Funding stream: NATIONAL LIBRARY OF MEDICINE
Communities
Digital Humanities and Cultural Heritage
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