Explainable Ensemble Learning With Stain Normalization and Deep Feature Extraction for Acute Lymphoblastic Leukaemia Classification.
Machine learning accurately identifies blood cancer cells from routine microscopy images, streamlining diagnostic workflows.
Explainable ensemble learning with stain normalization and deep feature extraction achieves high classification accuracy for ALL vs healthy cells on peripheral blood smear images. This record was retained from the prior triage attempt for PubMed pipeline handoff.
What the study was
- Study design
- algorithmic evaluation on blood smear image dataset
- Category
- cbc_diagnostics_ml
- Maturity
- Validated
- Journal
- Healthc Technol Lett
Why it surfaced
Explainable AI approach for ALL classification from blood smears—directly relevant to CBC/hematology ML topic—with emphasis on stain normalization robustness and XAI interpretability.
A plain-language summary of published research — not medical advice. Talk to a clinician about your own care.