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