Title:Big Data for Treatment Planning: Pathways and Possibilities for Smart
Healthcare Systems
Volume: 19
Author(s): Samiya Khan*, Shoaib Amin Banday and Mansaf Alam
Affiliation:
- School of Mathematics and Computer Science, University of Wolverhampton, Wolverhampton, United Kingdom
Keywords:
Big data, treatment planning, medical informatics, medical imaging, translational bioinformatics, smart healthcare.
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.
