BACKGROUND: Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research. OBJECTIVES: To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. METHODS: On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, which reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field. RESULTS: The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology. CONCLUSIONS: Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers.
BACKGROUND: Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research. OBJECTIVES: To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. METHODS: On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, which reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field. RESULTS: The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology. CONCLUSIONS: Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers.
Authors: Muhammed A Yildirim; Kwang-Il Goh; Michael E Cusick; Albert-László Barabási; Marc Vidal Journal: Nat Biotechnol Date: 2007-10 Impact factor: 54.908
Authors: Jack Y Yang; Andrzej Niemierko; Ruzena Bajcsy; Dong Xu; Brian D Athey; Aidong Zhang; Okan K Ersoy; Guo-Zheng Li; Mark Borodovsky; Joe C Zhang; Hamid R Arabnia; Youping Deng; A Keith Dunker; Yunlong Liu; Arif Ghafoor Journal: BMC Genomics Date: 2010-12-01 Impact factor: 3.969
Authors: A S Fialho; L A Celi; F Cismondi; S M Vieira; S R Reti; J M C Sousa; S N Finkelstein Journal: Methods Inf Med Date: 2013-08-28 Impact factor: 2.176