UMBC ebiquity

MTLD: Interpreting Medical Tables as Linked Data

Status: Past project

Project Description:

Evidence-based medicine is the application of current medical evidence to patient care and typically uses quantitative data from research studies. It is increasingly driven by data on the efficacy of drug dosages and the correlation between various medical factors that is assembled and integrated through meta--analyses (i.e., systematic reviews) of data in tables from publications and clinical trial studies. We describe a a key component of a system to produce evidence reports that performs two key functions: (i) understanding the meaning of data in clinical trial tables and (ii) identifying and retrieving relevant tables given a input query. We present modifications to our existing framework for inferring the semantics of tables and an ontology developed to model and represent clinical tables as RDF. Finally, we demonstrate how relevant tables can be identified by querying over their RDF representations and describe two evaluation experiments: one on mapping clinical tables to linked data and another on identifying tables relevant to a retrieval query.



MTO: Medical Tables Ontology
List of Query Strings used in Evaluation
Complete RDF for example table

Start Date: January 2014

End Date: January 2016

Principal Investigator:
Tim Finin
Anupam Joshi

Students:
Varish Mulwad

Tags: medical tables, linked data, clinical trial, meta-analysis, evidence-based medicine

 

There are 2 associated publications:  Hide the list...

2 Refereed Publications

2015

1. Varish Mulwad, "TABEL - A Domain Independent and Extensible Framework for Inferring the Semantics of Tables", PhdThesis, University of Maryland, Baltimore County, January 2015, 763 downloads.

2014

2. Varish Mulwad et al., "Interpreting Medical Tables as Linked Data to Generate Meta-Analysis Reports", InProceedings, Proceedings of the 15th IEEE International Conference on Information Reuse and Integration, August 2014, 474 downloads.

 

There are 0 associated resources:  Hide the list...

 

Research Areas:
 Medical informatics
 Semantic Web