Biological Data Mining


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Special section on biological data mining and its applications in healthcare

Sepsis is a major risk factor for patient death among those in intensive care not suffering from heart problems.

An introduction into Data Mining in Bioinformatics.

In fact, it is the eleventh cause of death overall in the USA. It arises when infection causes a breakdown in the immune system leading to a major inflammatory response.


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Research published in the International Journal of Data Mining and Bioinformatics suggests that infrared thermography could be used for the early detection of sepsis. Early detection is key to treating this condition and reducing the sepsis mortality rate [ Editor in Chief Prof. About this journal Editorial board Submitting articles.

Special section on biological data mining and its applications in healthcare

Readership IJDMB provides a forum to help academics, practitioners, post-graduates and policy makers, working in the area of data mining, data integration and management, bioinformatics, life sciences, healthcare, etc. Browse issues Vol.

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    Biological Interpretation/Tertiary Analysis

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    Access provided by: anon Sign Out. Preface to Biological Data Mining and its Applications in Healthcare Abstract: Scientists in biology and healthcare are facing an unprecedented growth of biological and clinical data such as genetic sequences, DNA micro arrays, bimolecular interactions and pathways, bio-images, patient records, and research papers. The new-found ease of generating large amounts of biological and clinical data has made the timely analysis of the data generated an uphill task.

    valiyaparamba.com/components/guqyseren/homme-black-gay.php In addition, to translate genomic research from bench to bedside, meaningful observations and discoveries will have to be drawn from a wide array of diverse data with high degrees of data heterogeneity and hierarchy, spanning from molecular biology to pharmaceutical and clinical domains.

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