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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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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
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author 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
author_facet 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
author_sort Coats, Thomas
collection PubMed
description 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.
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spelling pubmed-91756632022-07-14 An open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies 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 EJHaem Short Reports 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. John Wiley and Sons Inc. 2021-03-26 /pmc/articles/PMC9175663/ /pubmed/35845286 http://dx.doi.org/10.1002/jha2.182 Text en © 2021 The Authors. eJHaem published by British Society for Haematology and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Short Reports
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
An open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies
title An open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies
title_full An open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies
title_fullStr An open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies
title_full_unstemmed An open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies
title_short An open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies
title_sort open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies
topic Short Reports
url 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
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