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Erythrocyte Indices

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Hematological and biochemical parameters of Spix's Saddleback Tamarin (Leontocebus fuscicollis) raised in captivity.

Veterinaria italiana
The Spix's Saddleback Tamarin, Leontocebus fuscicollis is widely distributed across the Amazon region, but is endangered. This species is serving an important role in biomedical research in captivity. However, reference values for hematological and b...

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

Artificial intelligence in medicine
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...

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
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...

Using blood routine indicators to establish a machine learning model for predicting liver fibrosis in patients with Schistosoma japonicum.

Scientific reports
This study intends to use the basic information and blood routine of schistosomiasis patients to establish a machine learning model for predicting liver fibrosis. We collected medical records of Schistosoma japonicum patients admitted to a hospital i...

Support Vector Machine-Based Formula for Detecting Suspected α Thalassemia Carriers: A Path toward Universal Screening.

International journal of molecular sciences
The blood counts of α thalassemia carriers (α-thal) are similar to those of β thalassemia carriers, except for Hemoglobin A (Hb A), which is not elevated. The objective of this study was to determine whether mathematical formulas are effective for de...

Machine learning-based prediction of diabetic patients using blood routine data.

Methods (San Diego, Calif.)
Diabetes stands as one of the most prevalent chronic diseases globally. The conventional methods for diagnosing diabetes are frequently overlooked until individuals manifest noticeable symptoms of the condition. This study aimed to address this gap b...

MultiThal-classifier, a machine learning-based multi-class model for thalassemia diagnosis and classification.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: The differential diagnosis between iron deficiency anemia (IDA) and thalassemia trait (TT) remains a significant clinical challenge. This study aimed to develop a machine learning-based multi-class model to differentiate among Microcytic-...

Differential diagnosis of iron deficiency anemia from aplastic anemia using machine learning and explainable Artificial Intelligence utilizing blood attributes.

Scientific reports
As per world health organization, Anemia is a most prevalent blood disorder all over the world. Reduced number of Red Blood Cells or decrease in the number of healthy red blood cells is considered as Anemia. This condition also leads to the decrease ...

Associations between age, red cell distribution width and 180-day and 1-year mortality in giant cell arteritis patients: mediation analyses and machine learning in a cohort study.

Arthritis research & therapy
OBJECTIVE: The aim of this study was to investigate the correlation between age, red cell distribution width (RDW) levels, and 180-day and 1-year mortality in giant cell arteritis (GCA) patients hospitalized or admitted to the ICU.

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

Scientific reports
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...