Khan, Samiya ORCID: https://orcid.org/0000-0003-0837-5125, Banday, Shoaib Amin and Alam, Mansaf (2022) Big data for treatment planning: pathways and possibilities for smart healthcare systems. Current Medical Imaging, 19 (1). pp. 19-26. ISSN 1573-4056 (Print), 1875-6603 (Online) (doi:10.2174/1573405617666210917125642)

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Abstract

Background: Treatment planning is one of the crucial stages of healthcare assessment and delivery. Moreover, it also has a significant impact on patient outcomes and system efficiency. With the evolution of transformative healthcare technologies, most areas of healthcare have started collecting data at different levels, as a result of which there is a splurge in the size and complexity of health data being generated every minute.
Introduction: This paper explores the different characteristics of health data with respect to big data. Besides this, it also classifies research efforts in treatment planning on the basis of the informatics domain being used, which includes medical informatics, imaging informatics and translational bioinformatics.
Methods: This is a survey paper that reviews existing literature on the use of big data technologies for treatment planning in the healthcare ecosystem. Therefore, a qualitative research methodology was adopted for this work.
Results: Review of existing literature has been analyzed to identify potential gaps in research, identifying and providing insights into high prospect areas for potential future research.
Conclusion: The use of big data for treatment planning is rapidly evolving, and findings of this research can head start and streamline specific research pathways in the field.

Item Type:	Article
Uncontrolled Keywords:	Big data; medical imaging; medical informatics; smart healthcare; translational bioinformatics; treatment planning
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software R Medicine > RA Public aspects of medicine
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	23 Oct 2023 11:16
URI:	http://gala.gre.ac.uk/id/eprint/44582

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