Work

Predicting Type 1 Diabetes Onset using Novel Survival Analysis with Biomarker Ontology.

Year: 2020

Type: conference-paper

Abstract: . We applied this approach to a T1D dataset harmonized from three birth cohort studies from the United States, Finland, and Sweden. Results show that the dynamic biomarker patterns captured in the proposed ontology are able to improve prediction performance (in concordance index) by 5.3%, 3.3%, 2.8%, and 1.0% over baseline for 3, 6, 9, and 12 month duration windows, respectively.

Source: PubMed

Authors: Ying Li, Bin Liu, Vibha Anand, Jessica L Dunne, Markus Lundgren, Kenney Ng, Marian Rewers, Riitta Veijola, Mohamed Ghalwash

Institutions: IBM (United States), University of Oulu, Breakthrough T1D, Lund University, University of Colorado Denver

Language: English

Topic: Diabetes and associated disorders

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Institute of Diabetes and Digestive and Kidney Diseases

Awards: Natural History of Pre-Diabetic Autoimmunity (DAISY), University of Colorado Anschutz Medical Campus DRC

OpenAlex ID: W3157281852

FWCI:

Cites: 22

Cited by:

Related to: 10