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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...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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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. |
format | Online Article Text |
id | pubmed-9175663 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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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