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Final Activity Report Summary - BIOMED MINE (Galway Laboratory for Biomedical Data Mining)

This project has established and developed a new interdisciplinary research capability for Data Mining in Biomedical Science in the National University of Ireland Galway (NUIG). This is a new area of research expertise for the university. It has built on past research that has been conducted in NUIG here by the National Centre for Biomedical Engineering Science, the Medical Informatics Group, and the Data Mining & Machine Learning Group. Data mining involves a range of techniques that are concerned with extracting interesting knowledge from datasets that are typically large and unstructured. This knowledge can take the form of rules, patterns, structure or associations that summarise the whole dataset or relate to specific aspects of it. To be interesting they must be non-obvious, comprehensible, meaningful and potentially informative or useful. The field of data mining is strongly interlinked with that of machine learning, which is concerned with automatic development and refinement of hypotheses/models based on experience.

The specific research questions that have been addressed over the course of this project include:
A: Genomics: Identifying Patterns in Genomic Data.
B: Biophotonics: New paradigms for classification of Raman and fluorescence spectroscopy data.
C: Activities of Daily Living: Determining subjects' activities automatically though analysis of wearable sensors.
D: fMRI: Identification of Schizophrenia in subjects on the basis of functional magnetic resonance imaging scans E: Critical Care: Synthesis and analysis of multiple strands of temporal data from the bed-side, in support of medical decision-making.
F: Epigenetics: Understanding the mechanisms for drug resistance in cancer cells.

The project goals have been achieved through three principal work components:
1. Inward knowledge transfer, involving four Experienced Researchers conducting research in NUIG for extended periods: a) Dr Abdenour Bounsiar, b) Dr Ricardo Santiago-Mozos, c) Dr Mei Chen, d) Dr Imtiaz Khan.
2. Embedding of knowledge in the university and dissemination to the wider community, through seminars, publications, and a new website.
3. Development of research collaborations with leading international research groups through secondments of 3-5 months each by project participants, to: a) University of Helsinki, From Data To Knowledge research unit. b) University of California at Berkeley, Center for Intelligent Systems. c) University of California at Irvine, DataLab. d) Institute for Molecular Biology and Biotechnology, Iraklion, Crete.

The project has resulted in 21 peer-reviewed publications, as well as 9 international presentations, and participation in 11 conferences. It has also allowed members of the project team to secure follow-on funding from various programmes.

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