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 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.

Biomedical engineering R&D Fields:  Bioinformatics  Medical imaging  Image processing  Signal processing  Biomechanics  Biomaterials  Systems analysis  3-D modeling Products :  biocompatible prostheses  medical devices  diagnostic devices  Imaging equipment

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

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.

PUBMED RESOURCES Searching 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

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

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.

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

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.

OBO Relations: Foundational:  is_a  part_of Participation:  has_participant  has_agent Spatial:  located_in  contained_in  adjacent_to Temporal:  transformation_of  derives_from  preceded_by

Results:  Web site to create, modify and explore samples, collections and experiments

 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

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 s  Online repository of ppt converted to HTML  Semantic Web ?

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.

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

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.

BIBLIOGRAFY   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