AIMC Topic: Blood Cell Count

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Prediction of findings at screening colonoscopy using a machine learning algorithm based on complete blood counts (ColonFlag).

PloS one
Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- learning-based algorithm that uses basic patient information and complete blood cell counts (CBC) to identify individuals at elevated risk of colorectal c...

Correlations of Complete Blood Count with Alanine and Aspartate Transaminase in Chinese Subjects and Prediction Based on Back-Propagation Artificial Neural Network (BP-ANN).

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND The complete blood count (CBC) is the most common examination used to monitor overall health in clinical practice. Whether there is a relationship between CBC indexes and alanine transaminase (ALT) and aspartate aminotransferase (AST) has ...

Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting.

Sensors (Basel, Switzerland)
A lensless blood cell counting system integrating microfluidic channel and a complementary metal oxide semiconductor (CMOS) image sensor is a promising technique to miniaturize the conventional optical lens based imaging system for point-of-care test...

Evaluation of supervised machine-learning algorithms to distinguish between inflammatory bowel disease and alimentary lymphoma in cats.

Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc
Inflammatory bowel disease (IBD) and alimentary lymphoma (ALA) are common gastrointestinal diseases in cats. The very similar clinical signs and histopathologic features of these diseases make the distinction between them diagnostically challenging. ...

Danhong huayu koufuye prevents deep vein thrombosis through anti-inflammation in rats.

The Journal of surgical research
BACKGROUND: Danhong huayu koufuye (DHK) has traditionally been used clinically for a long time in China. This study was to evaluate the effect of DHK in treating deep vein thrombosis (DVT) in rats and explore its possible mechanism.

Clinical time series prediction: Toward a hierarchical dynamical system framework.

Artificial intelligence in medicine
OBJECTIVE: Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventi...

Leveraging Hematologic Single-Cell Measurements for Patient Triage and Outcome Prediction.

The journal of applied laboratory medicine
BACKGROUND: The complete blood count (CBC) is widely used across nearly all areas of medicine. While standard CBC markers reflect basic summaries of the blood cells, modern hematology analyzers generate many additional markers from the underlying dat...

Machine Learning Classifier Using Blood Count Parameters and Erythropoietin to Predict JAK2 Mutations in Patients With Erythrocytosis.

Archives of pathology & laboratory medicine
CONTEXT.—: Differentiating polycythemia vera from other causes of erythrocytosis is a diagnostic challenge. Although most patients with polycythemia vera have Janus kinase 2 (JAK2) mutations, extensive testing is impractical because this is an uncomm...

Impact of analytical bias on machine learning models for sepsis prediction using laboratory data.

Clinical chemistry and laboratory medicine
OBJECTIVES: Machine learning (ML) models, using laboratory data, support early sepsis prediction. However, analytical bias in laboratory measurements can compromise their performance and validity in real-world settings. We aimed to evaluate how analy...