CoTCoNet: An optimized coupled transformer-convolutional network with an adaptive graph reconstruction for leukemia detection
Background: Swift and accurate blood smear analyses are crucial for diagnosing leukemia
and other hematological malignancies. However, manual leukocyte count and …
and other hematological malignancies. However, manual leukocyte count and …
A hybrid detection model for acute lymphocytic leukemia using support vector machine and particle swarm optimization (SVM-PSO)
LK Alsaykhan, MS Maashi - Scientific Reports, 2024 - nature.com
Leukemia, a hematological disease affecting the bone marrow and white blood cells
(WBCs), ranks among the top ten causes of mortality worldwide. Delays in decision-making …
(WBCs), ranks among the top ten causes of mortality worldwide. Delays in decision-making …
Solving time cost optimization problem with adaptive multi-verse optimizer
VHS Pham, NT Nguyen Dang - OPSEARCH, 2024 - Springer
The construction industry holds a central role globally, marked by its unique attributes that
lead to distinct challenges. Given projects in this sector are often tailored to specific needs …
lead to distinct challenges. Given projects in this sector are often tailored to specific needs …
Fuzzy attention-based deep neural networks for acute lymphoblastic leukemia diagnosis
T Zhang, G Xue - Applied Soft Computing, 2025 - Elsevier
This research introduces the Fuzzy Squeeze-and-Excitation Densely Connected
Convolutional Networks with Orthogonal Projection Loss for precise diagnosis of Acute …
Convolutional Networks with Orthogonal Projection Loss for precise diagnosis of Acute …
A comprehensive study on Blood Cancer detection and classification using Convolutional Neural Network
Over the years in object detection several efficient Convolutional Neural Networks (CNN)
networks, such as DenseNet201, InceptionV3, ResNet152v2, SEresNet152, VGG19 …
networks, such as DenseNet201, InceptionV3, ResNet152v2, SEresNet152, VGG19 …
ODRNN: optimized deep recurrent neural networks for automatic detection of leukaemia
KD Shree, S Logeswari - Signal, Image and Video Processing, 2024 - Springer
Leukaemia image classification involves using machine learning, and often deep learning,
techniques to automatically analyse medical images and categorize them into different …
techniques to automatically analyse medical images and categorize them into different …
[HTML][HTML] Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia
Medical diagnosis plays a critical role in the early detection and treatment of diseases by
examining symptoms and supporting findings through advanced laboratory testing. Early …
examining symptoms and supporting findings through advanced laboratory testing. Early …
PCB defect detection based on pseudo-inverse transformation and YOLOv5
X Wang, SS Maidin, M Batumalay - PloS one, 2024 - journals.plos.org
With the development of integrated circuit packaging technology, the layout of printed circuit
boards has become complicated. Moreover, the traditional defect detection methods have …
boards has become complicated. Moreover, the traditional defect detection methods have …
High‐Accuracy and Lightweight Image Classification Network for Optimizing Lymphoblastic Leukemia Diagnosisy
L Mei, C Lian, S Han, S **, J He… - Microscopy …, 2025 - Wiley Online Library
Leukemia is a hematological malignancy that significantly impacts the human immune
system. Early detection helps to effectively manage and treat cancer. Although deep …
system. Early detection helps to effectively manage and treat cancer. Although deep …
[HTML][HTML] Integration of eye-tracking systems with sport concussion assessment tool 5th edition for mild TBI and concussion diagnostics in neurotrauma: Building a …
Abstract Traumatic Brain Injuries (TBIs), including mild TBI (mTBI) and concussions, affect an
estimated 69 million individuals annually with significant cognitive, physical, and …
estimated 69 million individuals annually with significant cognitive, physical, and …