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Machine learning in Huntington's disease: exploring the Enroll-HD dataset for prognosis and driving capability prediction.

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Title: Machine learning in Huntington's disease: exploring the Enroll-HD dataset for prognosis and driving capability prediction.
Authors: Ouwerkerk J; Department of Pathology and Clinical Bioinformatics, Erasmus Medical Center (EMC), Wytemaweg, 3015 CN, Rotterdam, The Netherlands., Feleus S; Department of Neurology, Leiden University Medical Center (LUMC), PO Box 9600, 2300 RC, Leiden, The Netherlands.; Department of Clinical Epidemiology, Leiden University Medical Center (LUMC), PO Box 9600, 2300 RC, Leiden, The Netherlands., van der Zwaan KF; Department of Neurology, Leiden University Medical Center (LUMC), PO Box 9600, 2300 RC, Leiden, The Netherlands., Li Y; Department of Pathology and Clinical Bioinformatics, Erasmus Medical Center (EMC), Wytemaweg, 3015 CN, Rotterdam, The Netherlands., Roos M; Department of Human Genetics, Leiden University Medical Center (LUMC), PO Box 9600, 2300 RC, Leiden, The Netherlands., van Roon-Mom WMC; Department of Human Genetics, Leiden University Medical Center (LUMC), PO Box 9600, 2300 RC, Leiden, The Netherlands., de Bot ST; Department of Neurology, Leiden University Medical Center (LUMC), PO Box 9600, 2300 RC, Leiden, The Netherlands., Wolstencroft KJ; Leiden Institute of Advanced Computer Science (LIACS), Leiden University, Niels Bohrweg 1, 2333 CA, Leiden, The Netherlands., Mina E; Department of Human Genetics, Leiden University Medical Center (LUMC), PO Box 9600, 2300 RC, Leiden, The Netherlands. e.mina@lumc.nl.
Source: Orphanet journal of rare diseases [Orphanet J Rare Dis] 2023 Jul 27; Vol. 18 (1), pp. 218. Date of Electronic Publication: 2023 Jul 27.
Publication Type: Observational Study; Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101266602 Publication Model: Electronic Cited Medium: Internet ISSN: 1750-1172 (Electronic) Linking ISSN: 17501172 NLM ISO Abbreviation: Orphanet J Rare Dis Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1750-1172
DOI:10.1186/s13023-023-02785-4