AIMC Topic: Leukemia, Myeloid, Acute
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Combining clinical and molecular data for personalized treatment in acute myeloid leukemia: A machine learning approach.
Computer methods and programs in biomedicine
Sep 18, 2024
BACKGROUND AND OBJECTIVE: The standard of care in Acute Myeloid Leukemia patients has remained essentially unchanged for nearly 40 years. Due to the complicated mutational patterns within and between individual patients and a lack of targeted agents ...
Artificial intelligence reveals the predictions of hematological indexes in children with acute leukemia.
BMC cancer
Aug 12, 2024
Childhood leukemia is a prevalent form of pediatric cancer, with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) being the primary manifestations. Timely treatment has significantly enhanced survival rates for children with acute ...
Machine learning-based biomarker screening for acute myeloid leukemia prognosis and therapy from diverse cell-death patterns.
Scientific reports
Aug 2, 2024
Acute myeloid leukemia (AML) exhibits pronounced heterogeneity and chemotherapy resistance. Aberrant programmed cell death (PCD) implicated in AML pathogenesis suggests PCD-related signatures could serve as biomarkers to predict clinical outcomes and...
CGMega: explainable graph neural network framework with attention mechanisms for cancer gene module dissection.
Nature communications
Jul 17, 2024
Cancer is rarely the straightforward consequence of an abnormality in a single gene, but rather reflects a complex interplay of many genes, represented as gene modules. Here, we leverage the recent advances of model-agnostic interpretation approach a...
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...
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