Kawazoe Y - Search Results

1

Computational Pipeline for Glomerular Segmentation and Association of the Quantified Regions with Prognosis of Kidney Function in IgA Nephropathy.

Kawazoe Y, Shimamoto K, Yamaguchi R, Nakamura I, Yoneda K, Shinohara E, Shintani-Domoto Y, Ushiku T, Tsukamoto T, Ohe K. Kawazoe Y, et al. Diagnostics (Basel). 2022 Nov 25;12(12):2955. doi: 10.3390/diagnostics12122955. Diagnostics (Basel). 2022. PMID: 36552963 Free PMC article.

2

Estimate of the pionic contribution to very forward electron scattering from 3He by surprisal analysis.

Kawazoe Y, Tsukamoto T. Kawazoe Y, et al. Phys Rev C Nucl Phys. 1986 Jan;33(1):275-277. doi: 10.1103/physrevc.33.275. Phys Rev C Nucl Phys. 1986. PMID: 9953138 No abstract available.

3

An ontology-based mediator of clinical information for decision support systems: a prototype of a clinical alert system for prescription.

Kawazoe Y, Ohe K. Kawazoe Y, et al. Methods Inf Med. 2008;47(6):549-59. doi: 10.3414/ME9126. Epub 2008 Nov 20. Methods Inf Med. 2008. PMID: 19020690

4

Prediction-based threshold for medication alert.

Kawazoe Y, Miyo K, Kurahashi I, Sakurai R, Ohe K. Kawazoe Y, et al. Stud Health Technol Inform. 2013;192:229-33. Stud Health Technol Inform. 2013. PMID: 23920550

5

A qualitative model for physiology: apart from function and abnormality.

Shinohara EY, Tatsukawa A, Kawazoe Y, Imai T, Ohe K. Shinohara EY, et al. Among authors: kawazoe y. Stud Health Technol Inform. 2013;192:984. Stud Health Technol Inform. 2013. PMID: 23920758

6

An analysis of the openehr archetype semantics based on a typed lambda theory.

Tatsukawa A, Shinohara EY, Kawazoe Y, Imai T, Ohe K. Tatsukawa A, et al. Among authors: kawazoe y. Stud Health Technol Inform. 2013;192:990. Stud Health Technol Inform. 2013. PMID: 23920764

7

Evaluation of a Context-based Prescription Alert System: A Clinical Perspective.

Miyo K, Kawazoe Y, Yamaguchi I, Tatsukawa A, Ohe K. Miyo K, et al. Among authors: kawazoe y. Stud Health Technol Inform. 2013;192:1030. Stud Health Technol Inform. 2013. PMID: 23920804

8

A Querying Method over RDF-ized Health Level Seven v2.5 Messages Using Life Science Knowledge Resources.

Kawazoe Y, Imai T, Ohe K. Kawazoe Y, et al. JMIR Med Inform. 2016 Apr 5;4(2):e12. doi: 10.2196/medinform.5275. JMIR Med Inform. 2016. PMID: 27050304 Free PMC article.

9

Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach.

Kagawa R, Kawazoe Y, Ida Y, Shinohara E, Tanaka K, Imai T, Ohe K. Kagawa R, et al. Among authors: kawazoe y. J Diabetes Sci Technol. 2017 Jul;11(4):791-799. doi: 10.1177/1932296816681584. Epub 2016 Dec 7. J Diabetes Sci Technol. 2017. PMID: 27932531 Free PMC article.

10

The Impact of "Possible Patients" on Phenotyping Algorithms: Electronic Phenotype Algorithms Can Only Be Reproduced by Sharing Detailed Annotation Criteria.

Kagawa R, Kawazoe Y, Shinohara E, Imai T, Ohe K. Kagawa R, et al. Among authors: kawazoe y. Stud Health Technol Inform. 2017;245:432-436. Stud Health Technol Inform. 2017. PMID: 29295131

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