Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Anita L. Lynam"'
Autor:
Anita L. Lynam, John M. Dennis, Katharine R. Owen, Richard A. Oram, Angus G. Jones, Beverley M. Shields, Lauric A. Ferrat
Publikováno v:
Diagnostic and Prognostic Research, Vol 4, Iss 1, Pp 1-10 (2020)
Abstract Background There is much interest in the use of prognostic and diagnostic prediction models in all areas of clinical medicine. The use of machine learning to improve prognostic and diagnostic accuracy in this area has been increasing at the
Externí odkaz:
https://doaj.org/article/7d83a1a064234f99b9609f39f40f094e
Publikováno v:
ICHI
Proceedings of the 8th IEEE International Conference on Healthcare Informatics
Proceedings of the 8th IEEE International Conference on Healthcare Informatics
The prevalence of obesity has increased worldwide in the past 50 years, reaching pandemic levels (Blüher, 2019). In this paper, we report on the development of an intervention evaluation model and risk assessment tool that has been developed for an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32a6f67f8ca6fd42b7dacb7df09ec8c5
https://doi.org/10.1109/ichi48887.2020.9374358
https://doi.org/10.1109/ichi48887.2020.9374358
Autor:
Martha Campbell-Thompson, Clive Wasserfall, Maria Beery, Richard A. Oram, Daniel J. Perry, Todd M. Brusko, Srikar Chamala, Irina Kusmartseva, Sarah J. Richardson, Angus G. Jones, Desmond A. Schatz, Christine Flaxman, Seth A. Sharp, Anita L. Lynam, Lauric A. Ferrat, Beverley M. Shields, Laura M. Jacobsen, Alice L. J. Carr, Mark A. Atkinson, Amanda L. Posgai
Publikováno v:
Diabet Med
AIMS Misclassification of diabetes is common due to an overlap in the clinical features of type 1 and type 2 diabetes. Combined diagnostic models incorporating clinical and biomarker information have recently been developed that can aid classificatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9129540c47ad8f3dcbc6e0d60f3e8f1
https://pubmed.ncbi.nlm.nih.gov/32634859
https://pubmed.ncbi.nlm.nih.gov/32634859
Autor:
Lauric A. Ferrat, Katharine R. Owen, Richard A. Oram, Beverley M. Shields, John M Dennis, Angus G. Jones, Anita L. Lynam
Publikováno v:
Diagnostic and Prognostic Research
Diagnostic and Prognostic Research, Vol 4, Iss 1, Pp 1-10 (2020)
Diagnostic and Prognostic Research, Vol 4, Iss 1, Pp 1-10 (2020)
Background There is much interest in the use of prognostic and diagnostic prediction models in all areas of clinical medicine. The use of machine learning to improve prognostic and diagnostic accuracy in this area has been increasing at the expense o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ed4ae1bcc5bf0ccf0af414836f92634
https://pubmed.ncbi.nlm.nih.gov/32607451
https://pubmed.ncbi.nlm.nih.gov/32607451
Autor:
Anita Hill, Timothy J. McDonald, Beverley M. Shields, Angus G. Jones, Michael N. Weedon, Anita L. Lynam, Richard A. Oram, Andrew T. Hattersley, Nicholas J. Thomas
Publikováno v:
Diabetologia
Aims/hypothesis Late-onset type 1 diabetes can be difficult to identify. Measurement of endogenous insulin secretion using C-peptide provides a gold standard classification of diabetes type in longstanding diabetes that closely relates to treatment r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bbb156f0bde9bd9e011c22f5a4360ce4
https://pubmed.ncbi.nlm.nih.gov/30969375
https://pubmed.ncbi.nlm.nih.gov/30969375
Autor:
John M Dennis, Anita L. Lynam, Andrew T. Hattersley, Beverley M. Shields, Timothy J. McDonald, Michael N. Weedon, Katharine R. Owen, Richard A. Oram, Angus G. Jones, Anita Hill, Ewan R. Pearson
Publikováno v:
BMJ Open
ObjectiveTo develop and validate multivariable clinical diagnostic models to assist distinguishing between type 1 and type 2 diabetes in adults aged 18–50.DesignMultivariable logistic regression analysis was used to develop classification models in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9955920dc012b8080521054ff758460
https://doi.org/10.1136/bmjopen-2019-031586
https://doi.org/10.1136/bmjopen-2019-031586