Health and Medical Analytics, through Analytical Focus and Contextualization, with New Challenges and Opportunities in the Context of Big Data

Research output: Contribution to journalReview article

Abstract

The central methodology here is Geometric Data Analysis, an alternative term for Correspondence Analysis, for analytics of processes and behaviours. The geometry of the factor space expresses semantics and implicit, underlying, relationships between what is observed or recorded and the attributes or variables that characterize them, and to this there may very well be clustering and that can very often be hierarchical clustering. This implies the processing here of data and information for analytics of processes and behaviours. Here, such processes and behaviours can be patient diagnosis and treatment, and also all that relates to health and that can give rise to the need for medical treatment. Also employed are practical applications from the work of eminent social scientist, Pierre Bourdieu. Also, at issue is the addressing of new societal challenges, and new themes and topics, problems and challenges, in medicine and in health and life sciences. Often achieved is to have relatively acceptable computational complexity.
LanguageEnglish
Pages488-493
Number of pages6
JournalEC Pharmacology and Toxicology
Volume7
Issue number6
Early online date31 May 2019
Publication statusPublished - Jun 2019

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Health
Correspondence Analysis
Life sciences
Hierarchical Clustering
Medicine
Data analysis
Computational Complexity
Express
Attribute
Clustering
Imply
Methodology
Alternatives
Term
Context
Semantics
Relationships

Cite this

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title = "Health and Medical Analytics, through Analytical Focus and Contextualization, with New Challenges and Opportunities in the Context of Big Data",
abstract = "The central methodology here is Geometric Data Analysis, an alternative term for Correspondence Analysis, for analytics of processes and behaviours. The geometry of the factor space expresses semantics and implicit, underlying, relationships between what is observed or recorded and the attributes or variables that characterize them, and to this there may very well be clustering and that can very often be hierarchical clustering. This implies the processing here of data and information for analytics of processes and behaviours. Here, such processes and behaviours can be patient diagnosis and treatment, and also all that relates to health and that can give rise to the need for medical treatment. Also employed are practical applications from the work of eminent social scientist, Pierre Bourdieu. Also, at issue is the addressing of new societal challenges, and new themes and topics, problems and challenges, in medicine and in health and life sciences. Often achieved is to have relatively acceptable computational complexity.",
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AB - The central methodology here is Geometric Data Analysis, an alternative term for Correspondence Analysis, for analytics of processes and behaviours. The geometry of the factor space expresses semantics and implicit, underlying, relationships between what is observed or recorded and the attributes or variables that characterize them, and to this there may very well be clustering and that can very often be hierarchical clustering. This implies the processing here of data and information for analytics of processes and behaviours. Here, such processes and behaviours can be patient diagnosis and treatment, and also all that relates to health and that can give rise to the need for medical treatment. Also employed are practical applications from the work of eminent social scientist, Pierre Bourdieu. Also, at issue is the addressing of new societal challenges, and new themes and topics, problems and challenges, in medicine and in health and life sciences. Often achieved is to have relatively acceptable computational complexity.

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