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Items: 5

1.

Predicting activities of daily living for cancer patients using an ontology-guided machine learning methodology.

Min H, Mobahi H, Irvin K, Avramovic S, Wojtusiak J.

J Biomed Semantics. 2017 Sep 16;8(1):39. doi: 10.1186/s13326-017-0149-6.

2.

Relating Complexity and Error Rates of Ontology Concepts. More Complex NCIt Concepts Have More Errors.

Min H, Zheng L, Perl Y, Halper M, De Coronado S, Ochs C.

Methods Inf Med. 2017 May 18;56(3):200-208. doi: 10.3414/ME16-01-0085. Epub 2017 Feb 28.

PMID:
28244549
3.

A Comprehensive Multimorbidity Index for Predicting Mortality in Intensive Care Unit Patients.

Min H, Avramovic S, Wojtusiak J, Khosla R, Fletcher RD, Alemi F, Elfadel Kheirbek R.

J Palliat Med. 2017 Jan;20(1):35-41. Epub 2016 Dec 7.

PMID:
27925837
4.

Scalable quality assurance for large SNOMED CT hierarchies using subject-based subtaxonomies.

Ochs C, Geller J, Perl Y, Chen Y, Xu J, Min H, Case JT, Wei Z.

J Am Med Inform Assoc. 2015 May;22(3):507-18. doi: 10.1136/amiajnl-2014-003151. Epub 2014 Oct 21.

5.

Sharing behavioral data through a grid infrastructure using data standards.

Min H, Ohira R, Collins MA, Bondy J, Avis NE, Tchuvatkina O, Courtney PK, Moser RP, Shaikh AR, Hesse BW, Cooper M, Reeves D, Lanese B, Helba C, Miller SM, Ross EA.

J Am Med Inform Assoc. 2014 Jul-Aug;21(4):642-9. doi: 10.1136/amiajnl-2013-001763. Epub 2013 Sep 27.

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