AIMC Topic: Precursor Cell Lymphoblastic Leukemia-Lymphoma
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Automatic detection and classification of leukocytes using convolutional neural networks.
Medical & biological engineering & computing
Nov 7, 2016
The detection and classification of white blood cells (WBCs, also known as Leukocytes) is a hot issue because of its important applications in disease diagnosis. Nowadays the morphological analysis of blood cells is operated manually by skilled opera...
Prediction of Allogeneic Hematopoietic Stem-Cell Transplantation Mortality 100 Days After Transplantation Using a Machine Learning Algorithm: A European Group for Blood and Marrow Transplantation Acute Leukemia Working Party Retrospective Data Mining Study.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
Aug 3, 2015
PURPOSE: Allogeneic hematopoietic stem-cell transplantation (HSCT) is potentially curative for acute leukemia (AL), but carries considerable risk. Machine learning algorithms, which are part of the data mining (DM) approach, may serve for transplanta...
Precursor Cell Lymphoblastic Leukemia-Lymphoma
Risk Factors
Kaplan-Meier Estimate
Logistic Models
Adult
Treatment Outcome
Leukemia, Myeloid, Acute
Disease-Free Survival
Europe
Male
Data Mining
Decision Trees
Decision Support Techniques
Middle Aged
Disease Progression
Hematopoietic Stem Cell Transplantation
Predictive Value of Tests
Humans
Retrospective Studies
Risk Assessment
Time Factors
Transplantation, Homologous
Area Under Curve
Machine Learning
Postoperative Complications
Female
ROC Curve
Registries
Algorithms
Reproducibility of Results
Explainable transformer-based deep survival analysis in childhood acute lymphoblastic leukemia.
Computers in biology and medicine
Jun 1, 2025
BACKGROUND: Acute lymphoblastic leukemia (ALL) is the most common type of leukemia among children and adolescents and can be life-threatening. The incidence of new cases has been increasing in recent years. Developing a predictive model to forecast t...
Evaluation of a machine-learning model based on laboratory parameters for the prediction of acute leukaemia subtypes: a multicentre model development and validation study in France.
The Lancet. Digital health
May 1, 2024
BACKGROUND: Acute leukaemias are life-threatening haematological cancers characterised by the infiltration of transformed immature haematopoietic cells in the blood and bone marrow. Prompt and accurate diagnosis of the three main acute leukaemia subt...
An Artificial Intelligence-Based Diagnostic System for Acute Lymphoblastic Leukemia Detection.
Studies in health technology and informatics
Jun 29, 2023
This study suggests a novel Acute Lymphoblastic Leukemia (ALL) diagnostic model, built solely on complete blood count (CBC) records. Using a dataset comprised of CBC records of 86 ALL and 86 control patients respectively, we identified the most ALL-s...
Modeling of the Acute Lymphoblastic Leukemia Detection by Convolutional Neural Networks (CNNs).
Current medical imaging
Jan 1, 2023
BACKGROUND: The techniques differed in many of the literature on the detection of Acute Lymphocytic Leukemia from the blood smear pictures, as the cases of infection in the world and the Kingdom of Saudi Arabia were increasing and the causes of this ...
ALLD: Acute Lymphoblastic Leukemia Detector.
Studies in health technology and informatics
Jan 14, 2022
Acute Lymphoblastic Leukemia (ALL) is a life-threatening type of cancer wherein mortality rate is unquestionably high. Early detection of ALL can reduce both the rate of fatality as well as improve the diagnosis plan for patients. In this study, we d...
AML, ALL, and CML classification and diagnosis based on bone marrow cell morphology combined with convolutional neural network: A STARD compliant diagnosis research.
Medicine
Nov 6, 2020
Leukemia diagnosis based on bone marrow cell morphology primarily relies on the manual microscopy of bone marrow smears. However, this method is greatly affected by subjective factors and tends to lead to misdiagnosis. This study proposes using bone ...
Analysis of Four Types of Leukemia Using Gene Ontology Term and Kyoto Encyclopedia of Genes and Genomes Pathway Enrichment Scores.
Combinatorial chemistry & high throughput screening
Jan 1, 2020
AIM AND OBJECTIVE: Leukemia is the second common blood cancer after lymphoma, and its incidence rate has an increasing trend in recent years. Leukemia can be classified into four types: acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML)...
Cytopathological image analysis using deep-learning networks in microfluidic microscopy.
Journal of the Optical Society of America. A, Optics, image science, and vision
Jan 1, 2017
Cytopathologic testing is one of the most critical steps in the diagnosis of diseases, including cancer. However, the task is laborious and demands skill. Associated high cost and low throughput drew considerable interest in automating the testing pr...
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