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James
G.
Mork
,
MS
Computer Scientist
Location: 
38A
/
09N915
Phone Number: (
301
827-4996
Expertise and Research Interests: 

Mr. Mork is currently the lead developer and technical project lead for the Medical Text Indexer (MTI) project.  The MTI project is a multi-divisional team developing the MTI program to assist indexers and catalogers in assigning keywords to over 600,000 biomedical related articles and books each year.  Mr. Mork’s research interests include information retrieval, natural language processing, and extracting information from biomedical literature.

Mr. Mork received his BS in Computer Science from Central Michigan University in 1984 and his MS in Computer Science from The Johns Hopkins University in 1988.

Mr. Mork’s previous experiences at Rapid Systems Solutions, Inc., Century Computing, Inc., VisionQuest Consulting, Inc., and previous Government employment have covered most aspects of Computer Science and Project Leadership.  His main focus has been on Rapid Application Prototyping.

Honors and Awards: 
  • 2016 - Frank B. Rogers Award recipient.
  • 2015 -  Library Operations Choice Awards Certificate of Appreciation for completing the study and policy change proposals to add preliminary MeSH indexing to In-Process citations to improve PubMed retrieval.
  • 2015 - Quality Step Increase for Sustained High Quality Work Performance.
  • 2014 - Recognition and Appreciation of Special Achievement for normalization of section headers within the MEDLINE structured abstracts.
  • 2013 - Library Operations Choice Awards Certificate of Appreciation for implementing an automated indexing process for the NLM Technical Bulletin.
  • 2011 - Exceptional Service by a Contractor for Medical Text Indexer First Line Prototype development.
  • 2011 – Special Act or Service Award for MTI as First Line Indexer Development and Pilot Production Project.
  • 2009 – Exceptional Service by a Contractor for Medical Text Indexer Catalog support.
  • 2008 – Special Act or Service Award for Medical Text Indexer Catalog support.
  • 2008 – Letter of Appreciation for Office of Director NIH Biennial Report support.
Publications/Tools by James Mork: 
Yepes AJ, Mork JG, Demner-Fushman D, Aronson AR. Comparison and combination of several MeSH indexing approaches. AMIA Annu Symp Proc. 2013 Nov 16;2013:709-18. eCollection 2013.
Jimeno-Yepes AJ, Plaza L, Mork JG, Aronson AR, Díaz A. MeSH indexing based on automatically generated summaries. BMC Bioinformatics. 2013 Jun 26;14:208. doi: 10.1186/1471-2105-14-208.
Jimeno-Yepes AJ, Sticco JC, Mork JG, Aronson AR. GeneRIF indexing: sentence selection based on machine learning. BMC Bioinformatics. 2013 May 31;14:171. doi: 10.1186/1471-2105-14-171.
Mork JG, Jimeno Yepes A, Aronson A. The NLM Medical Text Indexer System for Indexing Biomedical Literature. BioASQ 2013.
Jimeno Yepes A, Mork JG, Aronson A. Using the argumentative structure of scientific literature to improve information access. BioNLP 2013 (Poster).
Jimeno Yepes AJ, Mork JG, Aronson A. Identifying Publication Types Using Machine Learning. BioASQ Workshop 2013.
Jimeno-Yepes A, Mork J, Demner-Fushman D, Aronson AR. A one-size-fits-all indexing method does not exist: automatic selection based on meta-learning. JCSE, vol. 6, no. 2, pp.151-160, 2012.
Aronson AR, Mork J, Lang FM, Rogers W, Jimeno-Yepes A, Sticco JC. The NLM Indexing Initiative: Current Status and Role in Improving Access to Biomedical Information April 2012 Technical Report to the LHNCBC Board of Scientific Counselors.
Jimeno-Yepes A, Mork JG, Wilkowski B, Demner-Fushman D, Aronson AR. MEDLINE MeSH indexing: lessons learned from machine learning and future directions. Proc IHI 2012, 737-742.
Jimeno-Yepes A, Wilkowski B, Mork JG, Demner-Fushman D, Aronson AR. MeSH indexing: machine learning and lessons learned. ACM SIGHIT International Health Informatics Symposium, Miami, FL, USA, 2012.

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