The hemocompatibility of nanoparticles: a review of cell–nanoparticle interactions and hemostasis

KM de la Harpe, PPD Kondiah, YE Choonara… - Cells, 2019 - mdpi.com
Understanding cell–nanoparticle interactions is critical to develo** effective nanosized
drug delivery systems. Nanoparticles have already advanced the treatment of several …

Machine learning in detection and classification of leukemia using smear blood images: a systematic review

M Ghaderzadeh, F Asadi, A Hosseini… - Scientific …, 2021 - Wiley Online Library
Introduction. The early detection and diagnosis of leukemia, ie, the precise differentiation of
malignant leukocytes with minimum costs in the early stages of the disease, is a major …

Acute lymphoblastic leukemia detection and classification of its subtypes using pretrained deep convolutional neural networks

S Shafique, S Tehsin - Technology in cancer research & …, 2018 - journals.sagepub.com
Leukemia is a fatal disease of white blood cells which affects the blood and bone marrow in
human body. We deployed deep convolutional neural network for automated detection of …

Classification of acute lymphoblastic leukemia using deep learning

A Rehman, N Abbas, T Saba… - Microscopy …, 2018 - Wiley Online Library
Acute Leukemia is a life‐threatening disease common both in children and adults that can
lead to death if left untreated. Acute Lymphoblastic Leukemia (ALL) spreads out in children's …

Leukemia diagnosis in blood slides using transfer learning in CNNs and SVM for classification

LHS Vogado, RMS Veras, FHD Araujo… - … Applications of Artificial …, 2018 - Elsevier
Leukemia is a pathology that affects young people and adults, causing premature death and
several other symptoms. Computer-aided systems can be used to reduce the possibility of …

[HTML][HTML] Improving K-means clustering with enhanced Firefly Algorithms

H **e, L Zhang, CP Lim, Y Yu, C Liu, H Liu… - Applied Soft …, 2019 - Elsevier
In this research, we propose two variants of the Firefly Algorithm (FA), namely inward
intensified exploration FA (IIEFA) and compound intensified exploration FA (CIEFA), for …

White blood cells identification system based on convolutional deep neural learning networks

AI Shahin, Y Guo, KM Amin, AA Sharawi - Computer methods and …, 2019 - Elsevier
Background and objectives White blood cells (WBCs) differential counting yields valued
information about human health and disease. The current developed automated cell …

Deep learning approach to peripheral leukocyte recognition

Q Wang, S Bi, M Sun, Y Wang, D Wang, S Yang - PloS one, 2019 - journals.plos.org
Microscopic examination of peripheral blood plays an important role in the field of diagnosis
and control of major diseases. Peripheral leukocyte recognition by manual requires medical …

New segmentation and feature extraction algorithm for classification of white blood cells in peripheral smear images

S Tavakoli, A Ghaffari, ZM Kouzehkanan… - Scientific Reports, 2021 - nature.com
This article addresses a new method for the classification of white blood cells (WBCs) using
image processing techniques and machine learning methods. The proposed method …

An attention-based deep learning for acute lymphoblastic leukemia classification

M Jawahar, LJ Anbarasi, S Narayanan… - Scientific Reports, 2024 - nature.com
The bone marrow overproduces immature cells in the malignancy known as Acute
Lymphoblastic Leukemia (ALL). In the United States, about 6500 occurrences of ALL are …