AIMC Topic: Leukocytes

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Improved leukocyte classification in bone marrow cytology using convolutional neural network with contrast enhancement.

Scientific reports
Leukocytes or white blood cells (WBCs) are the main components of the immune system that protect the human body from various infections caused by viruses, bacteria, fungi, and other microorganisms. There are five major types of leukocytes: basophils,...

Machine learning based analysis of leucocyte cell population data by Sysmex XN series hematology analyzer for the diagnosis of bacteremia.

Scientific reports
In clinical practice, early recognition of bacteremia leads to prognostic improvement. Recently, cell population data (CPD) from the Sysmex XN-series hematology analyzer has attracted attention as a new method for the early diagnosis of bacteremia, b...

Domain-incremental white blood cell classification with privacy-aware continual learning.

Scientific reports
White blood cell (WBC) classification plays a vital role in hematology for diagnosing various medical conditions. However, it faces significant challenges due to domain shifts caused by variations in sample sources (e.g., blood or bone marrow) and di...

Domain knowledge-infused pre-trained deep learning models for efficient white blood cell classification.

Scientific reports
White blood cell (WBC) classification is a crucial step in assessing a patient's health and validating medical treatment in the medical domain. Hence, efficient computer vision solutions to the classification of WBC will be an effective aid to medica...

Multiscale deformed attention networks for white blood cell detection.

Scientific reports
White blood cell (WBC) detection is pivotal in medical diagnostics, crucial for diagnosing infections, inflammations, and certain cancers. Traditional WBC detection methods are labor-intensive and time-consuming. Convolutional Neural Networks (CNNs) ...

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning.

Scientific reports
Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailored treatment and prognosis. We used the MIMIC-IV database to analyze patients diagnosed with Sepsis-3 within 24 h of ICU admission. Latent class mixed...

Comparative Analysis of the Performance of Automated Digital Cell Morphology Analyzers for Leukocyte Differentiation in Hematologic Malignancies: Mindray MC-80 Versus West Medical Vision Hema.

International journal of laboratory hematology
INTRODUCTION: The use of artificial intelligence in hematology laboratories has improved the diagnostic evaluation of peripheral blood cells. The aim of this study is to compare the performance of two automated digital cell morphology analyzers, the ...

Identifying periphery biomarkers of first-episode drug-naïve patients with schizophrenia using machine-learning-based strategies.

Progress in neuro-psychopharmacology & biological psychiatry
Schizophrenia is a complex mental disorder. Accurate diagnosis and classification of schizophrenia has always been a major challenge in clinic due to the lack of biomarkers. Therefore, identifying molecular biomarkers, particularly in the peripheral ...

Two-stage CNN-based framework for leukocytes classification.

Computers in biology and medicine
Leukocytes are pivotal markers in health, crucial for diagnosing diseases like malaria and viral infections. Peripheral blood smear tests provide pathologists with vital insights into various medical conditions. Manual leukocyte counting is challengi...

Performance of the automated digital cell image analyzer UIMD PBIA in white blood cell classification: a comparative study with sysmex DI-60.

Clinical chemistry and laboratory medicine
OBJECTIVES: This study aimed to evaluate the performance of PBIA (UIMD, Seoul, Republic of Korea), an automated digital morphology analyzer using deep learning, for white blood cell (WBC) classification in peripheral blood smears and compare it with ...