ORCID Profile
0000-0002-6045-1781
Current Organisation
University of Southampton
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Publisher: Springer Science and Business Media LLC
Date: 21-04-2015
Publisher: Elsevier BV
Date: 12-2005
DOI: 10.1086/498396
Publisher: Wiley
Date: 05-2004
DOI: 10.1002/AJMG.A.20665
Abstract: Dense surface models can be used to analyze 3D facial morphology by establishing a correspondence of thousands of points across each 3D face image. The models provide dramatic visualizations of 3D face-shape variation with potential for training physicians to recognize the key components of particular syndromes. We demonstrate their use to visualize and recognize shape differences in a collection of 3D face images that includes 280 controls (2 weeks to 56 years of age), 90 in iduals with Noonan syndrome (NS) (7 months to 56 years), and 60 in iduals with velo-cardio-facial syndrome (VCFS 3 to 17 years of age). Ten-fold cross-validation testing of discrimination between the three groups was carried out on unseen test ex les using five pattern recognition algorithms (nearest mean, C5.0 decision trees, neural networks, logistic regression, and support vector machines). For discriminating between in iduals with NS and controls, the best average sensitivity and specificity levels were 92 and 93% for children, 83 and 94% for adults, and 88 and 94% for the children and adults combined. For in iduals with VCFS and controls, the best results were 83 and 92%. In a comparison of in iduals with NS and in iduals with VCFS, a correct identification rate of 95% was achieved for both syndromes. This article contains supplementary material, which may be viewed at the American Journal of Medical Genetics website at pages/0148-7299/suppmat/index.html.
Publisher: BMJ
Date: 05-02-2014
Publisher: Hindawi Limited
Date: 19-11-2015
DOI: 10.1002/HUMU.22924
Publisher: Springer Science and Business Media LLC
Date: 15-02-2019
DOI: 10.1038/S41467-019-08800-2
Abstract: The original version of this Article contained an error in the spelling of the author Laurence Faivre, which was incorrectly given as Laurence Faive. This has now been corrected in both the PDF and HTML versions of the Article.
Publisher: BMJ
Date: 07-2004
Publisher: Springer Science and Business Media LLC
Date: 25-01-2017
DOI: 10.1038/NATURE21062
Publisher: Springer Science and Business Media LLC
Date: 24-12-2014
DOI: 10.1038/NATURE14135
Publisher: Elsevier BV
Date: 03-2019
DOI: 10.1016/J.CELL.2019.02.040
Abstract: The introduction of exome sequencing in the clinic has sparked tremendous optimism for the future of rare disease diagnosis, and there is exciting opportunity to further leverage these advances. To provide diagnostic clarity to all of these patients, however, there is a critical need for the field to develop and implement strategies to understand the mechanisms underlying all rare diseases and translate these to clinical care.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Isabel Karen Temple.