ArticleFrontiers in public health2017
3-Dimensional Facial Analysis-Facing Precision Public Health.
Article in Frontiers in public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Fostering equity in precision health through diverse 3D facial data.Frontiers in medical technology · 2026Article
- Leaving no patient behind! Expert recommendation in the use of innovative technologies for diagnosing rare diseases.Orphanet journal of rare diseases · 2024Review
- Current and Future Advances in Surgical Therapy for Pituitary Adenoma.Endocrine reviews · 2023Article
- 3D facial analysis for rare disease diagnosis and treatment monitoring: Proof-Of-Concept plan for hereditary angioedema.PLOS digital health · 2023Article
- Innovation in Informatics to Improve Clinical Care and Drug Accessibility for Rare Diseases in China.Frontiers in pharmacology · 2021Article
- Barriers and Considerations for Diagnosing Rare Diseases in Indigenous Populations.Frontiers in pediatrics · 2020Review
- Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.Frontiers in genetics · 2019Article
- Optimizing Precision Medicine for Public Health.Frontiers in public health · 2019Review
- Big Data's Role in Precision Public Health.Frontiers in public health · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.