acePerson-Based Progression in Acute Myeloid Leukemia Classification: A Multi-View Convolutional Neural Network Approach
Acute myeloid leukemia (AML) is a hematologic malignancy in which accurate subtype identification is important for treatment planning and prognosis. This study developed a deep learning approach for AML subtype classification using multiple single-cell images from each patient rather than conventional instance-based classification. An open-source dataset containing 81,214 single-cell images from 189 individuals was analyzed. The dataset included four genetically defined AML subtypes and a healthy control group.…
Patient-level 500-view convolutional neural network improved acute myeloid leukemia subtype classification, achieving 0.8783 accuracy and 0.8622 F1 score compared to single-view analysis.
Evidence
- Peer-reviewedJournal of Imaging Informatics in Medicine2026-10-01
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Truvace Impact Record TRV-2026-1264, v1: “Person-Based Progression in Acute Myeloid Leukemia Classification: A Multi-View Convolutional Neural Network Approach.” Truvace, 2026-10-03. /record/TRV-2026-1264 (accessed at citation time). sha256 d6fa1bad5f79cb07…
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