Catalog Home Page

3-Dimensional Facial Analysis—Facing Precision Public Health

Baynam, G., Bauskis, A., Pachter, N., Schofield, L., Verhoef, H., Palmer, R.L., Kung, S., Helmholz, P., Ridout, M., Walker, C.E., Hawkins, A., Goldblatt, J., Weeramanthri, T.S., Dawkins, H.J.S. and Molster, C.M. (2017) 3-Dimensional Facial Analysis—Facing Precision Public Health. Frontiers in Public Health, 5 .

[img]
Preview
PDF - Published Version
Download (351kB) | Preview
Free to read: http://dx.doi.org/10.3389/fpubh.2017.00031
*No subscription required

Abstract

Precision public health is a new field driven by technological advances that enable more precise descriptions and analyses of individuals and population groups, with a view to improving the overall health of populations. This promises to lead to more precise clinical and public health practices, across the continuum of prevention, screening, diagnosis, and treatment. A phenotype is the set of observable characteristics of an individual resulting from the interaction of a genotype with the environment. Precision (deep) phenotyping applies innovative technologies to exhaustively and more precisely examine the discrete components of a phenotype and goes beyond the information usually included in medical charts. This form of phenotyping is a critical component of more precise diagnostic capability and 3-dimensional facial analysis (3DFA) is a key technological enabler in this domain. In this paper, we examine the potential of 3DFA as a public health tool, by viewing it against the 10 essential public health services of the “public health wheel,” developed by the US Centers for Disease Control. This provides an illustrative framework to gage current and emergent applications of genomic technologies for implementing precision public health.

Publication Type: Journal Article
Murdoch Affiliation: Centre for Comparative Genomics
Publisher: Frontiers Media
Copyright: © 2017 The Author(s).
URI: http://researchrepository.murdoch.edu.au/id/eprint/36571
Item Control Page Item Control Page

Downloads

Downloads per month over past year