Future Healthcare: Will Digital Data Lead to Better Care?
Main Article Content
Abstract
Currently, datasets used in bioinformatics and computational biology are high-dimensional, complex and multivariate. Analysis and processing of data is vital in medicine; however, manual analysis and pattern recognition with big data is difficult, and processing of large and weakly connected datasets is challenging. The increasing complexity of healthcare systems causes high health cost. To provide better healthcare services at reduced prices, computer-aided tools using smart approaches and context-aware computations are of great importance. Advancements in wireless network technology, mobile devices and pattern recognition applications help solve the cost problem of healthcare systems. In the future, patients will be able to participate in healthcare as their own health manager and observe important parameters like body fat amount and blood pressure. However, open issues related to this topic exist. In this paper, we present a survey of smart healthcare environments and smart hospitals and discuss some questions and challenges in this area.
Keywords: Future healthcare, healthcare system, smart hospitals, smart environments.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).