AIMC Topic: Neutrophils
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Predicting chemotherapy responsiveness in gastric cancer through machine learning analysis of genome, immune, and neutrophil signatures.
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Dec 2, 2024
BACKGROUND: Gastric cancer is a major oncological challenge, ranking highly among causes of cancer-related mortality worldwide. This study was initiated to address the variability in patient responses to combination chemotherapy, highlighting the nee...
Machine Learning Integration with Single-Cell Transcriptome Sequencing Datasets Reveals the Impact of Tumor-Associated Neutrophils on the Immune Microenvironment and Immunotherapy Outcomes in Gastric Cancer.
International journal of molecular sciences
Nov 26, 2024
The characteristics of neutrophils play a crucial role in defining the tumor inflammatory environment. However, the function of tumor-associated neutrophils (TANs) in tumor immunity and their response to immune checkpoint inhibitors (ICIs) remains in...
Prediction of the risk of mortality in older patients with coronavirus disease 2019 using blood markers and machine learning.
Frontiers in immunology
Nov 1, 2024
INTRODUCTION: The mortality rate among older people infected with severe acute respiratory syndrome coronavirus 2 is alarmingly high. This study aimed to explore the predictive value of a novel model for assessing the risk of death in this vulnerable...
Deep Learning-Based Blood Abnormalities Detection as a Tool for VEXAS Syndrome Screening.
International journal of laboratory hematology
Sep 14, 2024
INTRODUCTION: VEXAS is a syndrome described in 2020, caused by mutations of the UBA1 gene, and displaying a large pleomorphic array of clinical and hematological features. Nevertheless, these criteria lack significance to discriminate VEXAS from othe...
Immunohistochemistry annotations enhance AI identification of lymphocytes and neutrophils in digitized H&E slides from inflammatory bowel disease.
Computer methods and programs in biomedicine
Sep 13, 2024
BACKGROUND AND OBJECTIVE: Histologic assessment of the immune infiltrate in H&E slides is vital in diagnosing and managing inflammatory bowel diseases, but these assessments are subjective and time-consuming even for those with expertise. The develop...
Identification of neutrophil extracellular trap-related biomarkers in non-alcoholic fatty liver disease through machine learning and single-cell analysis.
Scientific reports
Sep 10, 2024
Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has become the leading chronic liver condition globally. Simultaneously, the annual disease burden, particularly liver cirrhosis caused by NAFLD, has increas...
Application of machine learning techniques in the diagnosis of endometriosis.
BMC women's health
Sep 5, 2024
OBJECTIVE: The aim of this study is to assess the use of machine learning methodologies in the diagnosis of endometriosis (EM).
Structured adaptive boosting trees for detection of multicellular aggregates in fluorescence intravital microscopy.
Microvascular research
Aug 13, 2024
Fluorescence intravital microscopy captures large data sets of dynamic multicellular interactions within various organs such as the lungs, liver, and brain of living subjects. In medical imaging, edge detection is used to accurately identify and deli...
Deep learning predicts the 1-year prognosis of pancreatic cancer patients using positive peritoneal washing cytology.
Scientific reports
Aug 2, 2024
Peritoneal washing cytology (CY) in patients with pancreatic cancer is mainly used for staging; however, it may also be used to evaluate the intraperitoneal status to predict a more accurate prognosis. Here, we investigated the potential of deep lear...
A self-supervised embedding of cell migration features for behavior discovery over cell populations.
Computer methods and programs in biomedicine
Jul 19, 2024
BACKGROUND AND OBJECTIVE: Recent studies point out that the dynamics and interaction of cell populations within their environment are related to several biological processes in immunology. Hence, single-cell analysis in immunology now relies on spati...
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