Browse by author
Lookup NU author(s): Dr Amir EnshaeiORCiD, Professor Anthony MoormanORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2026. Despite advances for patients with acute leukemia health disparities limit access to diagnosis and treatment. Artificial Intelligence (AI) approaches may address some disparities. We retrospectively assemble a diverse, international cohort of 6206 leukemia patients from 20 centers to test an AI tool designed to support leukemia diagnosis using standard laboratory results. Executing the pretrained algorithm results in varying accuracy metrics. With confidence cutoff predictions, 2000-fold bootstrapped area under the curve (AUROC) metrics are 0.94 for acute myeloid leukemia (AML), 0.98 for the promyelocytic subtype and 0.84 for acute lymphoblastic leukemia. However, this cutoff excludes 70.8–92.5% of patients from predictions. We improve accuracy and robustness, while maintaining generalizability via an ensemble of Isolation Forest and Local Outlier Factor increasing AUROC for AML from 0.72 to 0.84 (hold-out test set, patients below confidence threshold), while excluding only 12.1% of patients. Furthermore, we retrain the algorithm for pediatric patients.
Author(s): Turki AT, Fan Y, Hernandez-Sanchez A, Silva W, Fleming S, Yalcin K, Van Elssen CHMJ, Madanat Y, Karasek M, Aljurf M, Della Porta MG, Martinez-Roca A, Guarnera L, Steffen K, Antoniou E, Rivas MM, Mishra DK, Blum AT, Manantsoa SN, Adiat A, Enshaei A, Thol F, Voso MT, Chen J, Elhassan TA, Moorman AV, Vidriales MB, Neuendorff NR, Koc A, Mishra P, Strumberg D, Fourmanov RS, Heine L, Kleesiek J, Munarriz D, Asti G, Mokoonlall M, Kometas M, Rego E, Mecklenbrauck R, Sobas M, Wu D, Nensa F, Engelke M
Publication type: Article
Publication status: Published
Journal: Nature Communications
Year: 2026
Volume: 17
Online publication date: 20/03/2026
Acceptance date: 02/03/2026
Date deposited: 15/04/2026
ISSN (electronic): 2041-1723
Publisher: Springer Nature
URL: https://doi.org/10.1038/s41467-026-70584-z
DOI: 10.1038/s41467-026-70584-z
Data Access Statement: Anonymized acute leukemia laboratory data is deposited to the HARMONY Alliance data repository due to IRB restrictions. Data access can be requested by researchers in written form via office@harmony-alliance.eu (expected response time 2 weeks) and is subject to HARMONY data access committee approval. HARMONY will make data available for up to 12 months. Source data are provided with this paper. A demo dataset is provided with the GitHub code. Source data are provided in this paper.
PubMed id: 41856996
Altmetrics provided by Altmetric
