Special Issue on Foundations of Biomedical (Big) Data Science

Special Issue on Foundations of Biomedical (Big) Data Science

DescriptionThe concept of Big Data has gained a lot of attention during the last years. This term, which has been hardly discussed [1, 2], has emerged as a new viewpoint in which information can be handled. A prove of this phenomenon is the increasing adaptation and creation of new educational studies focused on Big Data, Data Science, Machine Learning, etc. Most of these terms have been widely studied in the last years due to the appearance of new approaches, techniques, and methodologies. Even when the study of these techniques and concepts have been notorious in many domains, it is in the biomedical one in which special attention has been paid.

A prove of this attention is the vast amount of papers related to Big Data in the health domain. In 2013, one of the first papers analyzing the revolution of Big Data and its application into the healthcare context was published in Journal of American Medical Association (JAMA) [3], discussing the application of Big Data to the healthcare sector under an economic perspective and highlighting the main opportunities and roadblocks. The paper focused on the importance of collecting data from patients and practitioners to improve the quality and efficiency of health care delivery.

In 2014, Costa et al. [4] discussed the breakthroughs achieved by the combination of omics and clinical health data as well as their applications to personalized medicine. Bates et al. [5] analyzed the use of Big Data for healthcare cost reducing in the US through six different cases (high-cost patients, readmissions, triage, decompensation, adverse events, and treatment optimization). Big Data has also been used for studies on reproducibility [6] and the management of privacy, security, data access, data governance, etc. [7]. In [6] the authors also conclude that a consequence of the Big Data scenario leads to the availability of new software, methods, and tools which will not only contribute to Big Data research but also might be beneficial for many biomedical informatics applications. In any case, all these concepts are still together, since they represent a natural evolution in the extraction and analysis of data, also in the biomedical domain. Special attention needs to be paid to the methodologies used and the results provided.

This special issue aims to attract papers based on (Big) Data Science technologies in the biomedical sector. We expect to receive papers that describe methodological approaches which clearly describes the methods and procedures used in the handling and analysis of the data used, as well as an explicit description of the data sources used, and the different processes applied to the data to provide a final system, framework or just analysis. Papers providing results in biomedical data analysis are also welcome, but the authors need to focus on the methodological design of the solution included in their analysis.

The topics to be covered include, but are not limited to:

  • Big Data and Analytics applied to healthcare management.

  • Legal, privacy and security issues related to Big Data.

  • New frameworks for the processing and analysis of biomedical information.

  • Methodologies, methods and tools applied to Biomedical Informatics field.

  • Data Science applied to biomedical information.

  • Unstructured biomedical information extraction and analysis.


[1] H. V. Jagadish, «Big Data and Science: Myths and Reality», Big Data Res., vol. 2, n.o 2, pp. 49-52, jun. 2015.
[2] Bonnie Feldman, Ellen M. Martin, y Tobi Skotnes, «Big Data in Healthcare Hype and Hope», oct. 2012.
[4] T. B. Murdoch y A. S. Detsky, «The inevitable application of big data to health care», JAMA, vol. 309, n.o 13, pp. 1351-1352, abr. 2013.
[5] F. F. Costa, «Big data in biomedicine», Drug Discov. Today, vol. 19, n.o 4, pp. 433-440, abr. 2014.
[6] D. W. Bates, S. Saria, L. Ohno-Machado, A. Shah, y G. Escobar, «Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients», Health Aff. (Millwood), vol. 33, n.o 7, pp. 1123-1131, jul. 2014.
[7] R. Bellazzi, «Big Data and Biomedical Informatics: A Challenging Opportunity», Yearb. Med. Inform., vol. 9, n.o 1, pp. 8-13, may 2014.
[8] J. Luo, M. Wu, D. Gopukumar, y Y. Zhao, «Big Data Application in Biomedical Research and Health Care: A Literature Review», Biomed. Inform. Insights, vol. 8, p. BII.S31559, ene. 2016.

Guest Editors:

  • Alejandro Rodríguez González, Universidad Politécnica de Madrid (Spain)
  • Sebastian Ventura Soto, Universidad de Córdoba (Spain)
  • Paolo Soda, University Campus Bio-Medico di Roma (Italy)