AIMC Topic: Leukemia, Myeloid, Acute
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Identification of hub genes and immune-related pathways in acute myeloid leukemia: insights from bioinformatics and experimental validation.
Frontiers in immunology
Jan 10, 2025
BACKGROUND: This study aims to identify the hub genes and immune-related pathways in acute myeloid leukemia (AML) to provide new theories for immunotherapy.
Why implementing machine learning algorithms in the clinic is not a plug-and-play solution: a simulation study of a machine learning algorithm for acute leukaemia subtype diagnosis.
EBioMedicine
Dec 24, 2024
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) algorithms have shown great promise in clinical medicine. Despite the increasing number of published algorithms, most remain unvalidated in real-world clinical settings. This study ai...
Classification of acute myeloid leukemia by pre-trained deep neural networks: A comparison with different activation functions.
Medical engineering & physics
Dec 10, 2024
Acute Myeloid Leukemia(AML) is a rapidly progressing cancer affecting blood and bone marrow, marked by the swift proliferation of abnormal myeloid cells. Effective treatment requires precise classification of AML subtypes. Conventional classification...
Differential impact of CD34+ cell dose for different age groups in allogeneic hematopoietic cell transplantation for acute leukemia: a machine learning-based discovery.
Experimental hematology
Nov 23, 2024
Allogeneic hematopoietic cell transplantation (allo-HCT) presents a potentially curative treatment for hematologic malignancies yet carries associated risks and complications. Continuous research focuses on predicting outcomes and identifying risk fa...
Automated workflow for the cell cycle analysis of (non-)adherent cells using a machine learning approach.
eLife
Nov 22, 2024
Understanding the cell cycle at the single-cell level is crucial for cellular biology and cancer research. While current methods using fluorescent markers have improved the study of adherent cells, non-adherent cells remain challenging. In this study...
Predictive modeling of outcomes in acute leukemia patients undergoing allogeneic hematopoietic stem cell transplantation using machine learning techniques.
Leukemia research
Nov 20, 2024
BACKGROUND: Leukemia necessitates continuous research for effective therapeutic techniques. Acute leukemia (AL) patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT) focus on key outcomes such as overall survival (OS), re...
Adolescent
Child, Preschool
Child
Graft vs Host Disease
Hematopoietic Stem Cell Transplantation
Treatment Outcome
Follow-Up Studies
Leukemia, Myeloid, Acute
Male
Middle Aged
Young Adult
Adult
Survival Rate
Prognosis
Retrospective Studies
Female
Aged
Transplantation, Homologous
Humans
Precursor Cell Lymphoblastic Leukemia-Lymphoma
Machine Learning
Leukemia
Bloodstream Infections in Childhood Acute Myeloid Leukemia and Machine Learning Models: A Single-institutional Analysis.
Journal of pediatric hematology/oncology
Oct 22, 2024
Childhood acute myeloid leukemia (AML) requires intensive chemotherapy, which may result in life-threatening bloodstream infections (BSIs). This study evaluated whether machine learning (ML) could predict BSI using electronic medical records. All chi...
Considerations for using tree-based machine learning to assess causation between demographic and environmental risk factors and health outcomes.
Environmental science and pollution research international
Oct 12, 2024
Evaluation of the heterogeneous treatment effect (HTE) allows for the assessment of the causal effect of a therapy or intervention while considering heterogeneity in individual factors within a population. Machine learning (ML) methods have previousl...
Machine learning based analysis of single-cell data reveals evidence of subject-specific single-cell gene expression profiles in acute myeloid leukaemia patients and healthy controls.
Biochimica et biophysica acta. Gene regulatory mechanisms
Oct 2, 2024
Acute Myeloid Leukaemia (AML) is characterized by uncontrolled growth of immature myeloid cells, disrupting normal blood production. Treatment typically involves chemotherapy, targeted therapy, and stem cell transplantation but many patients develop ...
BSNEU-net: Block Feature Map Distortion and Switchable Normalization-Based Enhanced Union-net for Acute Leukemia Detection on Heterogeneous Dataset.
Journal of imaging informatics in medicine
Sep 25, 2024
Acute leukemia is characterized by the swift proliferation of immature white blood cells (WBC) in the blood and bone marrow. It is categorized into acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), depending on whether the cell-lin...
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