AIMC Topic: Leukemia, Myeloid, Acute
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Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy.
eLife
Aug 5, 2021
For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrai...
Survival prognostic factors in patients with acute myeloid leukemia using machine learning techniques.
PloS one
Jul 21, 2021
This paper identifies prognosis factors for survival in patients with acute myeloid leukemia (AML) using machine learning techniques. We have integrated machine learning with feature selection methods and have compared their performances to identify ...
A deep learning model (ALNet) for the diagnosis of acute leukaemia lineage using peripheral blood cell images.
Computer methods and programs in biomedicine
Feb 12, 2021
BACKGROUND AND OBJECTIVES: Morphological differentiation among blasts circulating in blood in acute leukaemia is challenging. Artificial intelligence decision support systems hold substantial promise as part of clinical practise in detecting haematol...
Identification of drug combinations on the basis of machine learning to maximize anti-aging effects.
PloS one
Jan 28, 2021
Aging is a multifactorial process that involves numerous genetic changes, so identifying anti-aging agents is quite challenging. Age-associated genetic factors must be better understood to search appropriately for anti-aging agents. We utilized an ag...
A Reliable Machine Learning Approach applied to Single-Cell Classification in Acute Myeloid Leukemia.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Machine Learning research applied to the medical field is increasing. However, few of the proposed approaches are actually deployed in clinical settings. One reason is that current methods may not be able to generalize on new unseen instances which d...
IoMT-Based Automated Detection and Classification of Leukemia Using Deep Learning.
Journal of healthcare engineering
Dec 3, 2020
For the last few years, computer-aided diagnosis (CAD) has been increasing rapidly. Numerous machine learning algorithms have been developed to identify different diseases, e.g., leukemia. Leukemia is a white blood cells- (WBC-) related illness affec...
Leukemia, Myelogenous, Chronic, BCR-ABL Positive
Leukemia
Pattern Recognition, Automated
Precursor Cell Lymphoblastic Leukemia-Lymphoma
Algorithms
Cloud Computing
Humans
Databases, Factual
Leukemia, Lymphocytic, Chronic, B-Cell
Diagnostic Imaging
Neural Networks, Computer
Telemedicine
Leukemia, Myeloid, Acute
Machine Learning
Internet of Things
Diagnosis, Computer-Assisted
COVID-19
Deep Learning
MAGPEL: an autoMated pipeline for inferring vAriant-driven Gene PanEls from the full-length biomedical literature.
Scientific reports
Jul 23, 2020
In spite of the efforts in developing and maintaining accurate variant databases, a large number of disease-associated variants are still hidden in the biomedical literature. Curation of the biomedical literature in an effort to extract this informat...
Acute myeloid leukemia and artificial intelligence, algorithms and new scores.
Best practice & research. Clinical haematology
Jun 7, 2020
Artificial intelligence, and more narrowly machine-learning, is beginning to expand humanity's capacity to analyze increasingly large and complex datasets. Advances in computer hardware and software have led to breakthroughs in multiple sectors of ou...
A novel artificial intelligence protocol for finding potential inhibitors of acute myeloid leukemia.
Journal of materials chemistry. B
Feb 18, 2020
There is currently no effective treatment for acute myeloid leukemia, and surgery is also ineffective as an important treatment for most tumors. Rapidly developing artificial intelligence technology can be applied to different aspects of drug develop...
A novel one-class classification approach to accurately predict disease-gene association in acute myeloid leukemia cancer.
PloS one
Dec 11, 2019
Disease causing gene identification is considered as an important step towards drug design and drug discovery. In disease gene identification and classification, the main aim is to identify disease genes while identifying non-disease genes are of les...
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