AIMC Topic: Neutrophils
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Determination of optimum intensity and duration of exercise based on the immune system response using a machine-learning model.
Scientific reports
May 22, 2023
One of the important concerns in the field of exercise immunology is determining the appropriate intensity and duration of exercise to prevent suppression of the immune system. Adopting a reliable approach to predict the number of white blood cells (...
Deep-learning-based personalized prediction of absolute neutrophil count recovery and comparison with clinicians for validation.
Journal of biomedical informatics
Dec 10, 2022
Neutropenia and its complications are major adverse effects of cytotoxic chemotherapy. The time to recovery from neutropenia varies from patient to patient, and cannot be easily predicted even by experts. Therefore, we trained a deep learning model u...
Classification of peripheral blood neutrophils using deep learning.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Oct 29, 2022
Deep learning has been used to classify the while blood cells in peripheral blood smears. However, the classification of developing neutrophils is rarely studied. Moreover, it is still unknown whether deep learning can work well on the data coming fr...
Skeletal muscle regeneration with robotic actuation-mediated clearance of neutrophils.
Science translational medicine
Oct 6, 2021
Mechanical stimulation (mechanotherapy) can promote skeletal muscle repair, but a lack of reproducible protocols and mechanistic understanding of the relation between mechanical cues and tissue regeneration limit progress in this field. To address th...
Decreased neutrophil-mediated bacterial killing in COVID-19 patients.
Scandinavian journal of immunology
Jun 11, 2021
The coronavirus disease COVID-19 was first described in December 2019. The peripheral blood of COVID-19 patients have increased numbers of neutrophils which are important in controlling the bacterial infections observed in COVID-19. We sought to eval...
Blood Biomarkers Predict Cardiac Workload Using Machine Learning.
BioMed research international
Jun 1, 2021
INTRODUCTION: Rate pressure product (the product of heart rate and systolic blood pressure) is a measure of cardiac workload. Resting rate pressure product (rRPP) varies from one individual to the next, but its biochemical/cellular phenotype remains ...
Using Unsupervised Machine Learning to Identify Age- and Sex-Independent Severity Subgroups Among Patients with COVID-19: Observational Longitudinal Study.
Journal of medical Internet research
May 27, 2021
BACKGROUND: Early detection and intervention are the key factors for improving outcomes in patients with COVID-19.
Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: a cross-sectional study based on machine learning.
BMC infectious diseases
Feb 18, 2021
BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a global pandemic that has raised worldwide concern. This study aims to investigate the correlation between the extent of lung infection and relevant clinical laboratory testing indicators in...
Comparison of MPL-ANN and PLS-DA models for predicting the severity of patients with acute pancreatitis: An exploratory study.
The American journal of emergency medicine
Jan 22, 2021
OBJECTIVE: Acute pancreatitis (AP) is a common inflammatory disorder that may develop into severe AP (SAP), resulting in life-threatening complications and even death. The purpose of this study was to explore two different machine learning models of ...
Deep-Learning Based Label-Free Classification of Activated and Inactivated Neutrophils for Rapid Immune State Monitoring.
Sensors (Basel, Switzerland)
Jan 13, 2021
The differential count of white blood cells (WBCs) is one widely used approach to assess the status of a patient's immune system. Currently, the main methods of differential WBC counting are manual counting and automatic instrument analysis with labe...
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