AIMC Topic: Erythrocyte Indices

Clear Filters Showing 11 to 15 of 15 articles

Predictive value of red blood cell distribution width in septic shock patients with thrombocytopenia: A retrospective study using machine learning.

Journal of clinical laboratory analysis Oct 21, 2021
BACKGROUND: Sepsis-associated thrombocytopenia (SAT) is common in critical patients and results in the elevation of mortality. Red cell distribution width (RDW) can reflect body response to inflammation and oxidative stress. We try to investigate the...
Retrospective Studies Female Aged Machine Learning Prognosis Comorbidity Hospital Mortality Shock, Septic Male Middle Aged Humans Erythrocyte Indices Thrombocytopenia Propensity Score Kaplan-Meier Estimate
View on PubMed DOI

Identifying β-thalassemia carriers using a data mining approach: The case of the Gaza Strip, Palestine.

Artificial intelligence in medicine May 3, 2018
Thalassemia is considered one of the most common genetic blood disorders that has received excessive attention in the medical research fields worldwide. Under this context, one of the greatest challenges for healthcare professionals is to correctly d...
Asymptomatic Diseases Heterozygote Genetic Carrier Screening Middle East Erythrocyte Indices beta-Thalassemia Hemoglobins Data Mining Biomarkers Reproducibility of Results Predictive Value of Tests Bayes Theorem Decision Trees Humans Neural Networks, Computer Phenotype Databases, Factual
View on PubMed DOI

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

PloS one Feb 5, 2016
BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took acco...
Nutrition Surveys Data Mining Bilirubin Machine Learning Multivariate Analysis Erythrocyte Indices Algorithms Adolescent Biomarkers Blood Glucose Humans Logistic Models Aged, 80 and over Male Young Adult Depressive Disorder Middle Aged Adult Female Aged
View on PubMed DOI

Machine learning approach for differentiating iron deficiency anemia and thalassemia using random forest and gradient boosting algorithms.

Scientific reports May 15, 2025
Formulas based on red blood cell indices have been used to differentiate between iron deficiency anemia (IDA) and thalassemia (Thal). However, they exhibit varying efficiencies. In this study, we aimed to develop a tool for discriminating between IDA...
Machine Learning Adolescent Algorithms ROC Curve Diagnosis, Differential Young Adult Adult Male Erythrocyte Indices Random Forest Female Middle Aged Thalassemia Anemia, Iron-Deficiency Humans Boosting Machine Learning Algorithms
View on PubMed DOI

Evaluation of five discriminating indexes to distinguish Beta-Thalassemia Trait from Iron Deficiency Anaemia.

JPMA. The Journal of the Pakistan Medical Association Dec 1, 2016
OBJECTIVE: To assess the reliability of different red blood cell indices-based formulae in the indexes formula in differential diagnosis of beta thalassemia trait and iron deficiency anaemia.
beta-Thalassemia Male Diagnosis, Differential Reproducibility of Results Humans Pakistan Anemia, Iron-Deficiency Cross-Sectional Studies Erythrocyte Indices Female
View on PubMed
Popular Topics
Recent Journals