Please use this identifier to cite or link to this item:
https://doi.org/10.1038/srep17854
Title: | The Assessment of the Readiness of Molecular Biomarker-Based Mobile Health Technologies for Healthcare Applications | Authors: | Qin C. Tao L. Phang Y.H. Zhang C. Chen S.Y. Zhang P. Tan Y. Jiang Y.Y. Chen Y.Z. |
Keywords: | biological marker disease management health care delivery human information processing mass screening medical technology meta analysis molecular diagnosis personalized medicine procedures prognosis telemedicine Automatic Data Processing Biomarkers Biomedical Technology Delivery of Health Care Disease Management Humans Mass Screening Molecular Diagnostic Techniques Precision Medicine Prognosis Telemedicine |
Issue Date: | 2015 | Citation: | Qin C., Tao L., Phang Y.H., Zhang C., Chen S.Y., Zhang P., Tan Y., Jiang Y.Y., Chen Y.Z. (2015). The Assessment of the Readiness of Molecular Biomarker-Based Mobile Health Technologies for Healthcare Applications. Scientific Reports 5 : 17854. ScholarBank@NUS Repository. https://doi.org/10.1038/srep17854 | Abstract: | Mobile health technologies to detect physiological and simple-Analyte biomarkers have been explored for the improvement and cost-reduction of healthcare services, some of which have been endorsed by the US FDA. Advancements in the investigations of non-invasive and minimally-invasive molecular biomarkers and biomarker candidates and the development of portable biomarker detection technologies have fuelled great interests in these new technologies for mhealth applications. But apart from the development of more portable biomarker detection technologies, key questions need to be answered and resolved regarding to the relevance, coverage, and performance of these technologies and the big data management issues arising from their wide spread applications. In this work, we analyzed the newly emerging portable biomarker detection technologies, the 664 non-invasive molecular biomarkers and the 592 potential minimally-invasive blood molecular biomarkers, focusing on their detection capability, affordability, relevance, and coverage. Our analysis suggests that a substantial percentage of these biomarkers together with the new technologies can be potentially used for a variety of disease conditions in mhealth applications. We further propose a new strategy for reducing the workload in the processing and analysis of the big data arising from widespread use of mhealth products, and discuss potential issues of implementing this strategy. | Source Title: | Scientific Reports | URI: | https://scholarbank.nus.edu.sg/handle/10635/174569 | ISSN: | 2045-2322 | DOI: | 10.1038/srep17854 |
Appears in Collections: | Staff Publications Elements |
Show full item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
10_1038_srep17854.pdf | 1.97 MB | Adobe PDF | OPEN | Published | View/Download |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.