AIMC Topic: Leukemia, Myeloid, Acute
Clear Filters Showing 31 to 40 of 83 articles
Detection of acute promyelocytic leukemia in peripheral blood and bone marrow with annotation-free deep learning.
Scientific reports
Feb 13, 2023
While optical microscopy inspection of blood films and bone marrow aspirates by a hematologist is a crucial step in establishing diagnosis of acute leukemia, especially in low-resource settings where other diagnostic modalities are not available, the...
Epidemiological Features of Acute Myeloid Leukemia in Five Regions of the Republic of Kazakhstan: Population Study.
Asian Pacific journal of cancer prevention : APJCP
Dec 1, 2022
OBJECTIVE: The aim of the study was to assess the main epidemiological characteristics of AML (morbidity, survival, distribution by AML variants and age groups) in 5 regions participating in the study.
Explainable artificial intelligence for precision medicine in acute myeloid leukemia.
Frontiers in immunology
Sep 29, 2022
Artificial intelligence (AI) can unveil novel personalized treatments based on drug screening and whole-exome sequencing experiments (WES). However, the concept of "black box" in AI limits the potential of this approach to be translated into the clin...
Application of High Throughput Technologies in the Development of Acute Myeloid Leukemia Therapy: Challenges and Progress.
International journal of molecular sciences
Mar 5, 2022
Acute myeloid leukemia (AML) is a complex hematological malignancy characterized by extensive heterogeneity in genetics, response to therapy and long-term outcomes, making it a prototype example of development for personalized medicine. Given the acc...
LeuFeatx: Deep learning-based feature extractor for the diagnosis of acute leukemia from microscopic images of peripheral blood smear.
Computers in biology and medicine
Jan 19, 2022
The abnormal growth of leukocytes causes hematologic malignancies such as leukemia. The clinical assessment methods for the diagnosis of the disease are labor-intensive and time-consuming. Image-based automated diagnostic systems can be of great help...
Unsupervised discovery of dynamic cell phenotypic states from transmitted light movies.
PLoS computational biology
Dec 30, 2021
Identification of cell phenotypic states within heterogeneous populations, along with elucidation of their switching dynamics, is a central challenge in modern biology. Conventional single-cell analysis methods typically provide only indirect, static...
How to predict relapse in leukemia using time series data: A comparative in silico study.
PloS one
Nov 15, 2021
Risk stratification and treatment decisions for leukemia patients are regularly based on clinical markers determined at diagnosis, while measurements on system dynamics are often neglected. However, there is increasing evidence that linking quantitat...
Job characteristics of a Malaysian bank's anti-money laundering system and its employees' job satisfaction.
F1000Research
Oct 15, 2021
Banks and financial institutions are vulnerable to money laundering (ML) as a result of crime proceeds infiltrating banks in the form of significant cash deposits. Improved financial crime compliance processes and systems enable anti-ML (AML) analys...
Deep learning detects acute myeloid leukemia and predicts NPM1 mutation status from bone marrow smears.
Leukemia
Sep 8, 2021
The evaluation of bone marrow morphology by experienced hematopathologists is essential in the diagnosis of acute myeloid leukemia (AML); however, it suffers from a lack of standardization and inter-observer variability. Deep learning (DL) can proces...
Identification of biomarkers for acute leukemia via machine learning-based stemness index.
Gene
Aug 16, 2021
Traditional methods to understand leukemia stem cell (LSC)'s biological characteristics include constructing LSC-like cells and mouse models by transgenic or knock-in methods. However, there are some potential pitfalls in using this method, such as r...
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