Scientific Programming

Healthcare Big Data Management and Analytics in Scientific Programming


Publishing date
01 Aug 2020
Status
Published
Submission deadline
20 Mar 2020

Lead Editor

1University of Swabi, Swabi, Pakistan

2Complutense University of Madrid, Madrid, Spain

3University Putra Malaysia, Selangor, Malaysia

4Islamia College, Khyber Pakhtunkhwa, Pakistan


Healthcare Big Data Management and Analytics in Scientific Programming

Description

Healthcare systems are being digitally transformed by technological enhancements in medical information systems, electronic medical records, wearable and smart devices, and handheld devices. This increase in medical big data, alongside the development of computational techniques in the field of healthcare, has enabled researchers and practitioners to extract and visualize medical big data in a new spectrum.

Scientific programming will play a key role in providing solutions to existing and future problems involved in the management of large scale data in healthcare, such as by assisting in the processing of huge data volumes, complex system modelling, and sourcing derivations from healthcare data and simulations. Programming tools, including Apache Hadoop, Informatica PowerCenter, and Tableau, analyze data extremely efficiently and enable the visualization of meaningful insights extracted from big data. Visualization will be a key tool in creating images, diagrams, or animations by which to communicate healthcare messages and enhance understanding.

This Special Issue invites original research articles and review articles that explore the integration of big data and healthcare from a scientific programming perspective. Research that considers technological and computational barriers to big data management is particularly welcome.

Potential topics include but are not limited to the following:

  • Scientific programming tools, such as Apache Hadoop and Informatica PowerCenter used for large-scale data management and storage in healthcare
  • Data warehouse and knowledge representation in healthcare technologies
  • Scientific programming for medical big data visualization and representation
  • Accurate decision support systems for big data in healthcare
  • Machine and/or deep learning algorithms and applications in big data analytics for healthcare
  • Data mining in IoT and healthcare systems
  • Probabilistic computing approaches to the management of big data in healthcare
Scientific Programming
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Acceptance rate7%
Submission to final decision126 days
Acceptance to publication29 days
CiteScore1.700
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