AIMC Topic: Leukemia, Myeloid, Acute
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Machine learning and integrative multi-omics network analysis for survival prediction in acute myeloid leukemia.
Computers in biology and medicine
Jun 13, 2024
BACKGROUND: Acute myeloid leukemia (AML) is the most common malignant myeloid disorder in adults and the fifth most common malignancy in children, necessitating advanced technologies for outcome prediction.
Imaging Flow Cytometry and Convolutional Neural Network-Based Classification Enable Discrimination of Hematopoietic and Leukemic Stem Cells in Acute Myeloid Leukemia.
International journal of molecular sciences
Jun 12, 2024
Acute myeloid leukemia (AML) is a heterogenous blood cancer with a dismal prognosis. It emanates from leukemic stem cells (LSCs) arising from the genetic transformation of hematopoietic stem cells (HSCs). LSCs hold prognostic value, but their molecul...
Machine learning analysis of gene expression reveals TP53 Mutant-like AML with wild type TP53 and poor prognosis.
Blood cancer journal
May 14, 2024
Deep learning assists in acute leukemia detection and cell classification via flow cytometry using the acute leukemia orientation tube.
Scientific reports
Apr 9, 2024
This study aimed to evaluate the sensitivity of AI in screening acute leukemia and its capability to classify either physiological or pathological cells. Utilizing an acute leukemia orientation tube (ALOT), one of the protocols of Euroflow, flow cyto...
AML leukocyte classification method for small samples based on ACGAN.
Biomedizinische Technik. Biomedical engineering
Mar 29, 2024
Leukemia is a class of hematologic malignancies, of which acute myeloid leukemia (AML) is the most common. Screening and diagnosis of AML are performed by microscopic examination or chemical testing of images of the patient's peripheral blood smear. ...
MAGIC-DR: An interpretable machine-learning guided approach for acute myeloid leukemia measurable residual disease analysis.
Cytometry. Part B, Clinical cytometry
Feb 28, 2024
Multiparameter flow cytometry is widely used for acute myeloid leukemia minimal residual disease testing (AML MRD) but is time consuming and demands substantial expertise. Machine learning offers potential advancements in accuracy and efficiency, but...
Broadening the horizon: potential applications of CAR-T cells beyond current indications.
Frontiers in immunology
Nov 27, 2023
Engineering immune cells to treat hematological malignancies has been a major focus of research since the first resounding successes of CAR-T-cell therapies in B-ALL. Several diseases can now be treated in highly therapy-refractory or relapsed condit...
Automated Deep Learning-Based Diagnosis and Molecular Characterization of Acute Myeloid Leukemia Using Flow Cytometry.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Nov 3, 2023
The current flow cytometric analysis of blood and bone marrow samples for diagnosis of acute myeloid leukemia (AML) relies heavily on manual intervention in the processing and analysis steps, introducing significant subjectivity into resulting diagno...
Development and external validation of the multichannel deep learning model based on unenhanced CT for differentiating fat-poor angiomyolipoma from renal cell carcinoma: a two-center retrospective study.
Journal of cancer research and clinical oncology
Sep 6, 2023
PURPOSE: There are undetectable levels of fat in fat-poor angiomyolipoma. Thus, it is often misdiagnosed as renal cell carcinoma. We aimed to develop and evaluate a multichannel deep learning model for differentiating fat-poor angiomyolipoma (fp-AML)...
AMLnet, A deep-learning pipeline for the differential diagnosis of acute myeloid leukemia from bone marrow smears.
Journal of hematology & oncology
Mar 21, 2023
Acute myeloid leukemia (AML) is a deadly hematological malignancy. Cellular morphology detection of bone marrow smears based on the French-American-British (FAB) classification system remains an essential criterion in the diagnosis of hematological m...
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