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Research Article
Novel Incremental Ranking Framework for Biomedical Data Analytics and Dimensionality Reduction: Big Data Challenges and Opportunities
Author(s): Emad Elsebakhi, Ognian Asparouhov and Rashid Al-AliEmad Elsebakhi, Ognian Asparouhov and Rashid Al-Ali
Currently, due to the availability of massive biomedical data on each individual, both healthcare and life Science is becoming data-driven. The input-attributes are structured/un-structured data with many challenges, including sparse-binary attributes with imbalanced outcomes, non-unique distributed structure and high-dimensional data, which hamper efforts to make a clinical decision in clinical practice. In recent decades, considerable effort has been made toward overcoming most of these challenges, but still there is an essential need for significant improvements in this field, especially after integrating both omics and phenotype data for future personalized medicine. These challenges motivate us to use the state-of-the-art of big data analytics and large-scale machine learning frameworks to confront most of the challenges and provide proper clinical solutions to assess physicians .. Read More»
DOI:
10.4172/jcsb.1000190
Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report