Machine learning to improve false-positive results in the Dutch newborn screening for congenital hypothyroidism
Objective: The Dutch Congenital hypothyroidism (CH) Newborn Screening (NBS) algorithm for thyroidal and central congenital hypothyroidism (CH-T and CH-C, respectively) is primarily based on determination of thyroxine (T4) concentrations in dried blood spots, followed by thyroid-stimulating hormone (TSH) and thyroxine-binding globulin (TBG) measurements enabling detection of both CH-T and CH-C, with a positive predictive value (PPV) of 21%. A calculated T4/TBG ratio serves as an indirect measure for free T4. The aim of this study is to investigate whether machine learning techniques can help to... Mehr ...
Verfasser: |
Stroek, Kevin
Visser, Allerdien
van der Ploeg, Catharina P. B.
Zwaveling-Soonawala, Nitash
Heijboer, Annemieke C.
Bosch, Annet M.
van Trotsenburg, A. S. Paul
Boelen, Anita
Hoogendoorn, Mark
de Jonge, Robert |
Dokumenttyp: |
Artikel |
Erscheinungsdatum: |
2023 |
Reihe/Periodikum: |
Stroek , K , Visser , A , van der Ploeg , C P B , Zwaveling-Soonawala , N , Heijboer , A C , Bosch , A M , van Trotsenburg , A S P , Boelen , A , Hoogendoorn , M & de Jonge , R 2023 , ' Machine learning to improve false-positive results in the Dutch newborn screening for congenital hypothyroidism ' , Clinical Biochemistry , vol. 116 , pp. 7-10 . https://doi.org/10.1016/j.clinbiochem.2023.03.001 |
Sprache: |
Englisch |
Permalink: |
https://search.fid-benelux.de/Record/base-26687557 |
Datenquelle: |
BASE;
Originalkatalog |
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Link(s) :
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https://research.vumc.nl/en/publications/015ce8b9-6b37-499a-9b95-a6df52cea395 |