An open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies. Issue 2 (26th March 2021)

• Record Type: Journal Article
• Authors: 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
• Is Part Of: EJHaem. Volume 2:Issue 2(2021)
• Page Start: 261
• Page End: 265
• Publication Date: 2021-03-26
• Subjects: classifications -- clinical haematology -- diagnostic haematology -- myeloid leukaemia; Hematology -- Periodicals; 616.15
• DOI: 10.1002/jha2.182
• Languages: English
• ISSNs: 2688-6146

Abstract

Abstract: 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 .