advanced db systems biomedical engineering

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ADVANCED DB SYSTEMS ADVANCED DB SYSTEMS BIOMEDICAL ENGINEERING BIOMEDICAL ENGINEERING

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ADVANCED DB SYSTEMS BIOMEDICAL ENGINEERING. Index. INTRODUCTION BIOMEDICAL ENGINEERING B.E. DATASETS APPLICATIONS DATA MINING ON FDA DATABASE ONTOLOGY-BASED IMAGE-CENTERED TISSUE BANK SEMANTIC WEB –BASED SYSTEM IN ORAL MEDICINE CONCLUSION. BIOMEDICAL ENGINEERING INTRODUCTION. - PowerPoint PPT Presentation

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Page 1: ADVANCED DB SYSTEMS BIOMEDICAL ENGINEERING

ADVANCED DB SYSTEMSADVANCED DB SYSTEMS

BIOMEDICAL ENGINEERINGBIOMEDICAL ENGINEERING

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IndexINTRODUCTION BIOMEDICAL ENGINEERING B.E. DATASETS

APPLICATIONS DATA MINING ON FDA DATABASE ONTOLOGY-BASED IMAGE-CENTERED

TISSUE BANK SEMANTIC WEB –BASED SYSTEM IN

ORAL MEDICINE

CONCLUSION

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BIOMEDICAL ENGINEERING INTRODUCTION

Biomedical engineering is the application of engineering principles and techniques to the medical field.

It combines the design and problem solving skills of engineering with medical and biological sciences to help improving patient health care and the quality of life of individuals.

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Biomedical engineering R&D

Fields: Bioinformatics Medical imaging Image processing Signal processing Biomechanics Biomaterials Systems analysis 3-D modeling

Products :biocompatible prosthesesmedical devicesdiagnostic devicesImaging

equipment

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Recent advances in measurement techniques and computer hardware have enabled the collection of huge amount of biomedical data.

Patient records, digitalized image archives, DNA microarrays: the complexity of these data made analyses difficult and time-consuming.

BIOMEDICAL ENGINEERING DATASETS

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Biomedical datasets features:

• high-dimensionality

• small sample sizes

Example: a DNA microarray dataset might only have a hundred samples, but each sample can have 50,000 or more attributes.

Challenge to the data mining because most existing algorithms only work well on data in large quantity, but with a reasonable number of attributes or dimensions.

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PUBMED RESOURCESSearching terms to get knowledge about

applications in the medical field through PubMed, the results are

Data Mining: 4801 articles (644 in 2008) Ontology: 2940 articles (698 in 2008) Semantic Web: 319 articles (90 in 2008)

One recent example for each topic follows

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Four Data Mining algorithms were applied on the Food and Drug Administration database in which are stored adverse events of pharmaceutical drug

risk of hepatotoxicity associate with the use of Telithromycin

clinicians should be cautious when selecting telithromycin for treatment of an infection

DATA MINING ON FDA DATABASE

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ONTOLOGY-BASED IMAGE-CENTERED

TISSUE BANK

Tissue MicroArray (TMA) technique produces many images which need to be properly managed and possibly shared between institutes.

TMA consists of paraffin block in which up to 1000 separate tissue cores are assembled in array to allow simultaneous histological analysis.

At present, their utility is limited by the lack of data integration with biomolecular information.

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Four groups of data to support a TMA experiment: patients' clinical data sample origin, extraction and preservation TMA block aim and structure post-analysis image data

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Two ontology terms services were developed in order to describe

the pre-analysis tissue images the numerous post-process

analysis image.

Both are based on the the OBO (Open Biomedical Ontology) library, a repository of controlled vocabularies developed for shared use across different biological and medical domains.

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OBO Relations:

Foundational: is_a part_of

Participation: has_participanthas_agent

Spatial: located_in contained_in adjacent_to

Temporal: transformation_of derives_from preceded_by

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Results: Web site to create, modify and explore

samples, collections and experiments

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Complete identification and description of samples, crucial for tissue sharing Ontological terms allows the development of semantic web searches, improving data integration Possible integration with a full compliant gene ontology, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes

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SEMANTIC WEB – BASED SYSTEM IN ORAL MEDICINE

Participants of the Swedish Oral Medicine Network (SOMNet) discuss patient cases by means of:

Telephone PowerPoint presentations and emails

Online repository of ppt converted to HTML Semantic Web ?

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An online Semantic Web-based CoP (Communities of Practice), SOMWeb, was developed using OWL and RDF in order to formalize and structure case data and oral medicine knowledge.

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The system provides an opportunity for its members to share

high quality clinical practice knowledge external evidence related to complex oral

medicine cases

Use of SOMWeb: cases descriptions teleconference meetings online interviews and questionnaires

But it’s also a “bridge” between clinicians and researchers

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CONCLUSION

Biomedical engineering is a huge field in which are used accurate technologies to extract and use complex data.

Complexity of entities treated and abundance in terminology make formalization and structuring difficult.

Data mining and generalization on these kinds of data have to be careful because affect healthcare decisions.

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BIBLIOGRAFY

http://en.wikipedia.org/wiki/Biomedical_engineering Chen Y, Guo JJ, Healy DP, Lin X, Patel NC.

“Risk of hepatotoxicity associated with the use of telithromycin: a signal detection using data mining algorithms”, 2008 Nov 25

Viti F, Merelli I, Caprera A, Lazzari B, Stella A, Milanesi L.

“Ontology-based, Tissue MicroArray oriented, image centered tissue bank”, 2008 Apr 25

Falkman G, Gustafsson M, Jontell M, Torgersson O.

“SOMWeb: a semantic web-based system for supporting collaboration of distributed medical communities of practice”, 2008 Aug 26