[HTML][HTML] Demystifying supervised learning in healthcare 4.0: A new reality of transforming diagnostic medicine
The global healthcare sector continues to grow rapidly and is reflected as one of the fastest-
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …
Deep learning for the detection of acute lymphoblastic leukemia subtypes on microscopic images: A systematic literature review
Computer vision research in detecting and classifying the subtype Acute Lymphoblastic
Leukemia (ALL) has contributed to computer-aided diagnosis with improved accuracy …
Leukemia (ALL) has contributed to computer-aided diagnosis with improved accuracy …
Affine-consistent transformer for multi-class cell nuclei detection
Multi-class cell nuclei detection is a fundamental prerequisite in the diagnosis of
histopathology. It is critical to efficiently locate and identify cells with diverse morphology and …
histopathology. It is critical to efficiently locate and identify cells with diverse morphology and …
WBC YOLO-ViT: 2 Way-2 stage white blood cell detection and classification with a combination of YOLOv5 and vision transformer
SA Tarimo, MA Jang, EE Ngasa, HB Shin… - Computers in Biology …, 2024 - Elsevier
Accurate detection and classification of white blood cells, otherwise known as leukocytes,
play a critical role in diagnosing and monitoring various illnesses. However, conventional …
play a critical role in diagnosing and monitoring various illnesses. However, conventional …
Childhood leukemia classification via information bottleneck enhanced hierarchical multi-instance learning
Leukemia classification relies on a detailed cytomorphological examination of Bone Marrow
(BM) smear. However, applying existing deep-learning methods to it is facing two significant …
(BM) smear. However, applying existing deep-learning methods to it is facing two significant …
[HTML][HTML] A Step Towards Automated Haematology: DL Models for Blood Cell Detection and Classification
INTRODUCTION: Deep Learning has significantly impacted various domains, including
medical imaging and diagnostics, by enabling accurate classification tasks. This research …
medical imaging and diagnostics, by enabling accurate classification tasks. This research …
[HTML][HTML] An intelligent attention-based transfer learning model for accurate differentiation of bone marrow stains to diagnose hematological disorder
Bone marrow (BM) is an essential part of the hematopoietic system, which generates all of
the body's blood cells and maintains the body's overall health and immune system. The …
the body's blood cells and maintains the body's overall health and immune system. The …
Cellular nucleus image-based smarter microscope system for single cell analysis
W Wang, L Yang, H Sun, X Peng, J Yuan… - Biosensors and …, 2024 - Elsevier
Cell imaging technology is undoubtedly a powerful tool for studying single-cell
heterogeneity due to its non-invasive and visual advantages. It covers microscope …
heterogeneity due to its non-invasive and visual advantages. It covers microscope …
A state-of-the-art survey of artificial neural networks for whole-slide image analysis: from popular convolutional neural networks to potential visual transformers
In recent years, with the advancement of computer-aided diagnosis (CAD) technology and
whole slide image (WSI), histopathological WSI has gradually played a crucial aspect in the …
whole slide image (WSI), histopathological WSI has gradually played a crucial aspect in the …
[HTML][HTML] A soft label deep learning to assist breast cancer target therapy and thyroid cancer diagnosis
Simple Summary Early diagnosis and treatment of cancer is crucial for the survival of cancer
patients. Pathologists can use computational pathology techniques to make the diagnosis …
patients. Pathologists can use computational pathology techniques to make the diagnosis …