AIMC Topic: Blood Cell Count

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

The Journal of surgical research Nov 11, 2015
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.
Rats, Sprague-Dawley Blood Coagulation Thromboplastin Drugs, Chinese Herbal Tumor Necrosis Factor-alpha Interleukin-6 Matrix Metalloproteinase 9 Animals Drug Evaluation, Preclinical Male Venous Thrombosis Blood Cell Count Random Allocation Vena Cava, Inferior
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Clinical time series prediction: Toward a hierarchical dynamical system framework.

Artificial intelligence in medicine Nov 6, 2014
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...
Normal Distribution Predictive Value of Tests Cardiac Surgical Procedures Data Mining Humans Blood Cell Count Machine Learning Clinical Decision-Making Computer Simulation Time Factors Models, Statistical
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Development and validation of a machine learning model based on complete blood counts to predict clinical outcomes in urothelial carcinoma patients.

Clinica chimica acta; international journal of clinical chemistry Jul 15, 2025
Urothelial carcinoma (UC) is a highly malignant disease with significant public health implications. Despite advancements in oncology, early diagnosis and effective prognostic tools remain limited. This study aimed to develop a machine learning model...
Humans Machine Learning Prognosis Retrospective Studies Middle Aged Cohort Studies Urologic Neoplasms Blood Cell Count Female Aged Aged, 80 and over Male
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A Multianalyte Machine Learning Model to Detect Wrong Blood in Complete Blood Count Tube Errors in a Pediatric Setting.

Clinical chemistry Mar 3, 2025
BACKGROUND: Multianalyte machine learning (ML) models can potentially identify previously undetectable wrong blood in tube (WBIT) errors, improving upon current single-analyte delta check methodology. However, WBIT detection model performance has not...
Humans Machine Learning Child Blood Cell Count
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Machine learning algorithm approach to complete blood count can be used as early predictor of COVID-19 outcome.

Journal of leukocyte biology Feb 13, 2025
Although the SARS-CoV-2 infection has established risk groups, identifying biomarkers for disease outcomes is still crucial to stratify patient risk and enhance clinical management. Optimal efficacy of COVID-19 antiviral medications relies on early a...
Humans Machine Learning COVID-19 Adult Male Middle Aged Brazil Severity of Illness Index Female ROC Curve SARS-CoV-2 Monocytes Hospitalization Blood Cell Count Aged Algorithms Biomarkers Prognosis
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Machine Learning-Based Prediction of Hemoglobinopathies Using Complete Blood Count Data.

Clinical chemistry Aug 1, 2024
BACKGROUND: Hemoglobinopathies, the most common inherited blood disorder, are frequently underdiagnosed. Early identification of carriers is important for genetic counseling of couples at risk. The aim of this study was to develop and validate a nove...
Machine Learning Retrospective Studies Female Adult Humans Hemoglobinopathies Male ROC Curve Logistic Models Blood Cell Count
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[A preliminary prediction model of depression based on whole blood cell count by machine learning method].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine] Nov 6, 2023
This study used machine learning techniques combined with routine blood cell analysis parameters to build preliminary prediction models, helping differentiate patients with depression from healthy controls, or patients with anxiety. A multicenter stu...
Support Vector Machine Bayes Theorem Blood Cell Count Humans Machine Learning Depression
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Interpretable Estimation of Suicide Risk and Severity from Complete Blood Count Parameters with Explainable Artificial Intelligence Methods.

Psychiatria Danubina Jan 1, 2023
BACKGROUND: The peripheral inflammatory markers are important in the pathophysiology of suicidal behavior. However, methods for practical uses haven't been developed enough yet. This study developed predictive models based on explainable artificial i...
Adolescent Suicidal Ideation Suicide Models, Statistical Blood Cell Count Middle Aged Risk Assessment Suicide, Attempted Case-Control Studies Young Adult Adult Male Humans Artificial Intelligence Female Reproducibility of Results Aged Aged, 80 and over
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Deus Ex Machina? Predicting SARS-CoV-2 Infection from Lab Tests Using Machine Learning.

Clinical chemistry Nov 1, 2020
Humans Machine Learning Pandemics COVID-19 Algorithms Electronic Health Records SARS-CoV-2 Laboratories Betacoronavirus Probability Pneumonia, Viral Reverse Transcriptase Polymerase Chain Reaction Blood Cell Count Coronavirus Infections Clinical Laboratory Techniques COVID-19 Testing Programming Languages
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Hematological disturbances in Down syndrome: single centre experience of thirteen years and review of the literature.

The Turkish journal of pediatrics Jan 1, 2019
Karakurt N, Uslu İ, Aygün C, Albayrak C. Hematological disturbances in Down syndrome: single centre experience of thirteen years and review of the literature. Turk J Pediatr 2019; 61: 664-670. Neonates with Down syndrome (DS) may have hematological a...
Child, Preschool Infant, Newborn Child Blood Cell Count Risk Factors Humans Logistic Models Down Syndrome Male Retrospective Studies Follow-Up Studies Infant Hematologic Diseases Female
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