Deep learning model for differentiating acute myeloid and lymphoblastic leukemia in peripheral blood cell images via myeloblast and lymphoblast classification.
Sholhui ParkYoung Hoon ParkJungwon HuhSeung Min BaikDong-Jin ParkPublished in: Digital health (2024)
The performance of the developed ensemble model for the 12 cell classifications was satisfactory, particularly for myeloblasts and lymphoblasts. We believe that the application of our model will benefit healthcare settings where the rapid and accurate diagnosis of AL is difficult.
Keyphrases
- deep learning
- healthcare
- peripheral blood
- convolutional neural network
- single cell
- machine learning
- acute myeloid leukemia
- bone marrow
- cell therapy
- stem cells
- dendritic cells
- high resolution
- artificial intelligence
- computed tomography
- mass spectrometry
- social media
- respiratory failure
- health information
- hepatitis b virus
- sensitive detection