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An open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies

Accurate, reproducible diagnoses can be difficult to make in haemato‐oncology due to multi‐parameter clinical data, complex diagnostic criteria and time‐pressured environments. We have designed a decision tree application (DTA) that reflects WHO diagnostic criteria to support accurate diagnoses of m...

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Detalles Bibliográficos
Autores principales: Coats, Thomas, Bean, Daniel, Vatopoulou, Theodora, Vijayavalli, Dhanapal, El‐Bashir, Razan, Panopoulou, Aikaterini, Wood, Henry, Wimalachandra, Manujasri, Coppell, Jason, Medd, Patrick, Furtado, Michelle, Tucker, David, Kulasakeraraj, Austin, Pawade, Joya, Dobson, Richard, Ireland, Robin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9175663/
https://www.ncbi.nlm.nih.gov/pubmed/35845286
http://dx.doi.org/10.1002/jha2.182
Descripción
Sumario:Accurate, reproducible diagnoses can be difficult to make in haemato‐oncology due to multi‐parameter clinical data, complex diagnostic criteria and time‐pressured environments. We have designed a decision tree application (DTA) that reflects WHO diagnostic criteria to support accurate diagnoses of myeloid malignancies. The DTA returned the correct diagnoses in 94% of clinical cases tested. The DTA maintained a high level of accuracy in a second validation using artificially generated clinical cases. Optimisations have been made to the DTA based on the validations, and the revised version is now publicly available for use at http://bit.do/ADAtool.