Unsupervised machine learning algorithms identify expected haemorrhage relationships but define unexplained coagulation profiles mapping to thrombotic phenotypes in hereditary haemorrhagic telangiectasia

Hereditary haemorrhagic telangiectasia (HHT) can result in challenging anaemia and thrombosis phenotypes. Clinical presentations of HHT vary for relatives with identical casual mutations, suggesting other factors may modify severity. To examine objectively, we developed unsupervised machine learning...

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Detalles Bibliográficos
Autores principales: Mukhtar, Ghazel, Shovlin, Claire L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Sickle Cell, Thrombosis, and Classical Haematology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435691/
https://www.ncbi.nlm.nih.gov/pubmed/37601877
http://dx.doi.org/10.1002/jha2.746

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10435691/
https://www.ncbi.nlm.nih.gov/pubmed/37601877
http://dx.doi.org/10.1002/jha2.746

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