Journal of cellular and molecular medicine
May 1, 2025
Leukaemia stem cells (LSCs) are a rare population among the bulk of leukaemia cells and are responsible for disease initiation, progression/relapse and insensitivity to therapies in numerous haematologic malignancies. Identification of LSCs and monit...
Studies in health technology and informatics
Apr 8, 2025
Evaluating the blood smear test images remains the main route of detecting the type of leukaemia, accurate diagnosis is fundamental in providing effective treatment. The changes in the structure of the white blood cells present different morphologica...
OBJECTIVE: Leukemia is a type of blood cancer that begins in the bone marrow and results in high numbers of abnormal white blood cells. Automated detection and classification of leukemia and its subtypes using artificial intelligence (AI) and machine...
Leukemia is a serious problem affecting both children and adults, leading to death if left untreated. Leukemia is a kind of blood cancer described by the rapid proliferation of abnormal blood cells. An early, trustworthy, and precise identification o...
Medical image segmentation has numerous applications in diagnosing different diseases. Various types of diseases are found in white blood and Red blood cells. This paper represents the segmentation of WBCs from blood smear images. It is a complex and...
PURPOSE: Matching patients to clinical trials is cumbersome and costly. Attempts have been made to automate the matching process; however, most have used a trial-centric approach, which focuses on a single trial. In this study, we developed a patient...
Studies in health technology and informatics
Jun 29, 2022
The accuracy of smear test image classification is a fundamental aspect in differentiating the type of leukaemia and determining the right treatment to improve the patient's chances of survival and recovery. Image Classification has lately become a v...
Mathematical biosciences and engineering : MBE
Mar 14, 2022
Gene expression data is highly dimensional. As disease-related genes account for only a tiny fraction, a deep learning model, namely GSEnet, is proposed to extract instructive features from gene expression data. This model consists of three modules, ...
Journal of X-ray science and technology
Jan 1, 2022
BACKGROUND: Processing Low-Intensity Medical Images (LI-MI) is difficult as outcomes are varied when it comes to manual examination, which is also a time-consuming process.
This work shows the advantage of expert knowledge for leukemic cell recognition. In the medical area, visual analysis of microscopic images has regularly used biological samples to recognize hematological disorders. Nowadays, techniques of image reco...
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