AIMC Topic: Blood Cell Count

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Classification of α-thalassemia data using machine learning models.

Computer methods and programs in biomedicine
BACKGROUND: Around 7% of the global population has congenital hemoglobin disorders, with over 300,000 new cases of α-thalassemia annually. Diagnosis is costly and inaccurate in low-income regions, often relying on complete blood count (CBC) tests. Th...

Comparison between statistical and machine learning methods to detect the hematological indices with the greatest influence on elevated serum levels of low-density lipoprotein cholesterol.

Chemistry and physics of lipids
INTRODUCTION: Elevated levels of low-density lipoprotein-cholesterol (LDL-C) is a significant risk factor for the development of cardiovascular diseases (CVD)s. Furthermore, studies have revealed an association between indices of the complete blood c...

Unlocking the complete blood count as a risk stratification tool for breast cancer using machine learning: a large scale retrospective study.

Scientific reports
Optimizing early breast cancer (BC) detection requires effective risk assessment tools. This retrospective study from Brazil showcases the efficacy of machine learning in discerning complex patterns within routine blood tests, presenting a globally a...

Enhancing pneumonia prognosis in the emergency department: a novel machine learning approach using complete blood count and differential leukocyte count combined with CURB-65 score.

BMC medical informatics and decision making
BACKGROUND: Pneumonia poses a major global health challenge, necessitating accurate severity assessment tools. However, conventional scoring systems such as CURB-65 have inherent limitations. Machine learning (ML) offers a promising approach for pred...

Predicting community acquired bloodstream infection in infants using full blood count parameters and C-reactive protein; a machine learning study.

European journal of pediatrics
Early recognition of bloodstream infection (BSI) in infants can be difficult, as symptoms may be non-specific, and culture can take up to 48 h. As a result, many infants receive unneeded antibiotic treatment while awaiting the culture results. In thi...

Artificial intelligence and the blood film: Performance of the MC-80 digital morphology analyzer in samples with neoplastic and reactive cell types.

International journal of laboratory hematology
INTRODUCTION: Implementing artificial intelligence-based instruments in hematology laboratories requires evidence of efficiency in classifying pathological cells. In two-Universities, we assessed the performance of the Mindray® MC-80 for hematology p...

Performance analysis of the compact haematology analyser Sight OLO.

International journal of laboratory hematology
INTRODUCTION: Sight OLO is a compact full blood count (FBC) analyser that uses digital imaging techniques and artificial intelligence to count and assess cellular components of capillary or venous blood. It provides a FBC with a 5-part white blood ce...

Machine learning models outperform manual result review for the identification of wrong blood in tube errors in complete blood count results.

International journal of laboratory hematology
INTRODUCTION: Wrong blood in tube (WBIT) errors are a significant patient-safety issue encountered by clinical laboratories. This study assessed the performance of machine learning models for the identification of WBIT errors affecting complete blood...

A machine-learning parsimonious multivariable predictive model of mortality risk in patients with Covid-19.

Scientific reports
The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction mo...

Evaluation of Scopio Labs X100 Full Field PBS: The first high-resolution full field viewing of peripheral blood specimens combined with artificial intelligence-based morphological analysis.

International journal of laboratory hematology
BACKGROUND: Current digital cell imaging systems perform peripheral blood smear (PBS) analysis in limited regions of the PBS and require the support of manual microscopy without achieving full digital microscopy. We report a multicenter study that va...