'Unified medical language system' presentation slideshows

Ontology and the Future of Biomedical Research

Ontology and the Future of Biomedical Research. Barry Smith http://ifomis.org. Institute for Formal Ontology and Medical Information Science. Saarland University. From chromosome to disease. Problem:

1.9k views • 188 slides

Ontologies What, Why and How A Tutorial Tim Finin 28 April 2004 325b ITE Building, UMBC

Ontologies What, Why and How A Tutorial Tim Finin 28 April 2004 325b ITE Building, UMBC. http://ebiquity.umbc.edu/v2.1/resource/html/id/20/. Overview. Three questions about ontologies What are they? Why should we care? How can we build and use them?. Overview -- agenda.

1.94k views • 132 slides

SEMANTIC MATCH MAKING AND RANKING OF MEDICAL LITERATURE

SEMANTIC MATCH MAKING AND RANKING OF MEDICAL LITERATURE. By:Priya Wadhwa Major professor:Dr. Arpinar Committee:Dr. Ramaswamy Dr. Taha. Outline. Introduction Motivation Goals System Overview System Workflow Pillars Match Making Overview Document Ranking

981 views • 84 slides

Ontology Engineering for the Semantic Web and Beyond

1.28k views • 82 slides

What is Semantic Publishing? And Why Should I Care?

710 views • 60 slides

Pax Terminologica

718 views • 58 slides

Disease Informatics: Terms and Jargon to begin with

Disease Informatics: Terms and Jargon to begin with. R. P. Deolankar. General Terms. Data and Information. Data Numbers Words Images Information is derived from the data Information It is the knowledge derived from analysis of the data Inferences can be drawn from information

718 views • 49 slides

590 views • 42 slides

Literature Mining and Ontology BMI/IBGP 705 Winter, 2012

Literature Mining and Ontology BMI/IBGP 705 Winter, 2012. Yang Xiang, Ph.D. in Computer Science yxiang@bmi.osu.edu Department of Biomedical Informatics The Ohio State University. Outline. What is Literature Mining? Popular Tools for Literature Mining Basic Techniques

545 views • 42 slides

Statistical Predicate Invention

Statistical Predicate Invention. Stanley Kok Dept. of Computer Science and Eng. University of Washington Joint work with Pedro Domingos. Overview. Motivation Background Multiple Relational Clusterings Experiments Future Work. Motivation. Statistical Relational Learning.

450 views • 38 slides

Terminology, Classification and Ontology in the Biomedical Domain: Past, Present and Future

465 views • 36 slides

Ontologies and User Needs in Publishing

460 views • 34 slides

Applied Informatics

Applied Informatics. Health IT Standards Unit 2 Lesson 1. Lesson Overview. Lesson Objectives. At the end of this lesson, you will be able to: Recognize the needs for HIT standards

484 views • 33 slides

Semantic Interpretation of Medical Text

Semantic Interpretation of Medical Text. Barbara Rosario, SIMS Steve Tu, UC Berkeley Advisor: Marti Hearst, SIMS. Semantic Interpretation of Medical Text . More accurate representation of the content of the input text

656 views • 29 slides

Taxonomy of Nursing Diagnoses

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Taxonomy of Nursing Diagnoses

358 views • 21 slides

524 views • 17 slides

EQUALITY OF RETRIEVAL: Levelling the Metadata Playing Field in Big Indexes

EQUALITY OF RETRIEVAL: Levelling the Metadata Playing Field in Big Indexes. Aaron Wood Metadata Librarian Assistant Head, Technical Services Libraries and Cultural Resources University of Calgary aawood@ucalgary.ca. American Library Association 2010 Midwinter Meeting:

248 views • 17 slides

Strategies for Model-Oriented Information Organization

255 views • 15 slides

Medbiquitous 2009

Learners. Medbiquitous 2009. Subject Matter Experts. Educators. Digital Asset Management System. Informatics Expert. Instructional Designers. Application Developers. The Team. ASCP Asset Warehouse- Application Services. Taxonomy For Pathology Images; Asset Publishing Process.

268 views • 14 slides