AIMC Topic: Hemoglobins

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Non-invasive anemia detection from conjunctiva and sclera images using vision transformer with attention map explainability.

Scientific reports
Iron-deficiency anemia, a prevalent global health issue, traditionally requires invasive procedures for accurate diagnosis, such as a blood sample for measuring hemoglobin (Hgb) concentration. Nevertheless, this marker can be visually assessed by obs...

Machine learning improves detection of alpha thalassemia carriers compared to clinical features.

Scientific reports
Alpha-thalassemia is a widespread genetic disorder, and accurately distinguishing between alpha-plus (α⁺) and alpha-zero (α⁰) types is critical for effective screening and management. This study developed and evaluated machine learning models to clas...

A Machine Learning-Driven Cyclic Optimizing Strategy for the Construction of Paper-Based Microfluidic Devices in the Early Diagnosis of Periodontitis.

ACS sensors
The lack of effective optimization strategies hinders the optimal performance of paper-based microfluidic analytical devices (μPADs). In this work, a Machine Learning-driven Computer vision-BP Neural Networks-Genetic Algorithm-based Cyclic Optimizing...

Anemia prediction using gene expression programming (GEP) and explainable artificial intelligence approaches.

Computers in biology and medicine
Anemia being a global health disorder, affecting millions of people, especially pregnant women, children, and the elderly. Proper and timely diagnosis must be ensured to prevent its adverse effects, but the traditional diagnostic methods are very tim...

Clinical diagnostic and prognostic value of homocysteine combined with hemoglobin [f (Hcy-Hb)] in cardio-renal syndrome caused by primary acute myocardial infarction.

Journal of translational medicine
BACKGROUND: Cardio-renal syndrome (CRS), characterized by multi-organ interaction, is frequently overlooked in clinical practice. It poses significant challenges in treatment, leading to poor long-term prognosis and substantial economic burden on pat...

Prediction of gastrointestinal hemorrhage in cardiology inpatients using an interpretable XGBoost model.

Scientific reports
Gastrointestinal bleeding (GIB) occurs more frequently in cardiovascular patients than in the general population, significantly affecting morbidity and mortality. However, existing predictive models often lack sufficient accuracy and interpretability...

Inhibiting heme piracy by pathogenic Escherichia coli using de novo-designed proteins.

Nature communications
Iron is an essential nutrient for most bacteria and is often growth-limiting during infection, due to the host sequestering free iron as part of the innate immune response. To obtain the iron required for growth, many bacterial pathogens encode trans...

A novel method to predict the haemoglobin concentration after kidney transplantation based on machine learning: prediction model establishment and method optimization.

BMC medical informatics and decision making
BACKGROUND: Anaemia is a common complication after kidney transplantation, and the haemoglobin concentration is one of the main criteria for identifying anaemia. Moreover, artificial intelligence methods have developed rapidly in recent years, are wi...

Machine learning model and hemoglobin to red cell distribution width ratio evaluates all-cause mortality in pulmonary embolism.

Scientific reports
The ratio of hemoglobin (Hb) to red blood cell distribution width (RDW), known as HRR, functions as an innovative indicator related to prognosis. However, whether HRR can predict the mortality for pulmonary embolism (PE) patients remains ambiguous. A...

Machine reading and recovery of colors for hemoglobin-related bioassays and bioimaging.

Science advances
Despite advances in machine learning and computer vision for biomedical imaging, machine reading and learning of colors remain underexplored. Color consistency in computer vision, color constancy in human perception, and color accuracy in biomedical ...