A review on computer aided detection and classification of leukemia

KK Anilkumar, VJ Manoj, TM Sagi - Multimedia Tools and Applications, 2024 - Springer
Leukemia is a non-tumor type of cancer and its early diagnosis is important in the treatment
and prognosis. Image based diagnosis is quick and easy compared to the conventional …

Semantic Role Labeling for Information Extraction on Indonesian Texts: A Literature Review

ADP Ariyanto, C Fatichah… - … International Seminar on …, 2023 - ieeexplore.ieee.org
The information extraction process includes Semantic Role Labeling (SRL) as one of its sub-
tasks. SRL aims to determine the semantic role of each entity within a sentence by …

A review on leukemia detection and classification using Artificial Intelligence-based techniques

AE Aby, S Salaji, KK Anilkumar, T Rajan - Computers and Electrical …, 2024 - Elsevier
Leukemia is a type of cancer affecting blood-forming tissues, where timely diagnosis is
crucial for early intervention and better treatment outcomes. Traditional detection methods …

[HTML][HTML] Deep learning enhances acute lymphoblastic leukemia diagnosis and classification using bone marrow images

B Elsayed, M Elhadary, RM Elshoeibi… - Frontiers in …, 2023 - frontiersin.org
Acute lymphoblastic leukemia (ALL) poses a significant health challenge, particularly in
pediatric cases, requiring precise and rapid diagnostic approaches. This comprehensive …

The Art of YOLOv8 Algorithm in Cancer Diagnosis using Medical Imaging

N Palanivel, S Deivanai… - … Conference on System …, 2023 - ieeexplore.ieee.org
Cancer continues to be a global health challenge, demanding innovative solutions to
improve early detection and treatment outcomes. This research project harnesses the power …

[HTML][HTML] Hybrid Feature-Learning-Based PSO-PCA Feature Engineering Approach for Blood Cancer Classification

G Atteia, R Alnashwan, M Hassan - Diagnostics, 2023 - mdpi.com
Acute lymphoblastic leukemia (ALL) is a lethal blood cancer that is characterized by an
abnormal increased number of immature lymphocytes in the blood or bone marrow. For …

CDC-NET: a cell detection and confirmation network of bone marrow aspirate images for the aided diagnosis of AML

J Su, Y Liu, J Zhang, J Han, J Song - Medical & Biological Engineering & …, 2024 - Springer
Standardized morphological evaluation in pathology is usually qualitative. Classifying and
qualitatively analyzing the nucleated cells in the bone marrow aspirate images based on …

[HTML][HTML] Advancing Early Leukemia Diagnostics: A Comprehensive Study Incorporating Image Processing and Transfer Learning

R Haque, A Al Sakib, MF Hossain, F Islam… - …, 2024 - mdpi.com
Disease recognition has been revolutionized by autonomous systems in the rapidly
developing field of medical technology. A crucial aspect of diagnosis involves the visual …

Detection of chronic lymphocytic leukemia using Deep Neural Eagle Perch Fuzzy Segmentation–A novel comparative approach

A Ashwini, SR Sriram, JJJ Sheela - Biomedical Signal Processing and …, 2024 - Elsevier
With a high mortality rate worldwide, Chronic Lymphocytic Leukemia (CLL) poses a serious
health risk. Radiologists view the ability to detect blood tumor cells as both important and …

Deep and Machine Learning for Acute Lymphoblastic Leukemia Diagnosis: A Comprehensive Review

M Faiz, BG Mounika, M Akbar… - ADCAIJ: Advances in …, 2024 - revistas.usal.es
The medical condition known as acute lymphoblastic leukemia (ALL) is characterized by an
excess of immature lymphocyte production, and it can affect people across all age ranges …