AIMC Topic: C-Reactive Protein
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Prediction of the risk of mortality in older patients with coronavirus disease 2019 using blood markers and machine learning.
Frontiers in immunology
Nov 1, 2024
INTRODUCTION: The mortality rate among older people infected with severe acute respiratory syndrome coronavirus 2 is alarmingly high. This study aimed to explore the predictive value of a novel model for assessing the risk of death in this vulnerable...
Using random forest and biomarkers for differentiating COVID-19 and Mycoplasma pneumoniae infections.
Scientific reports
Sep 30, 2024
The COVID-19 pandemic has underscored the critical need for precise diagnostic methods to distinguish between similar respiratory infections, such as COVID-19 and Mycoplasma pneumoniae (MP). Identifying key biomarkers and utilizing machine learning t...
Prediction of gestational diabetes mellitus by multiple biomarkers at early gestation.
BMC pregnancy and childbirth
Sep 16, 2024
BACKGROUND: It remains unclear which early gestational biomarkers can be used in predicting later development of gestational diabetes mellitus (GDM). We sought to identify the optimal combination of early gestational biomarkers in predicting GDM in m...
Adiponectin
Sex Hormone-Binding Globulin
Insulin-Like Growth Factor Binding Protein 2
Predictive Value of Tests
C-Reactive Protein
Pregnancy Trimester, First
Fibronectins
Diabetes, Gestational
Biomarkers
Pregnancy
Female
Adult
Case-Control Studies
China
Humans
Blood Glucose
Machine Learning
ROC Curve
Insulin-Like Growth Factor I
Logistic Models
Investigating artificial intelligence models for predicting joint pain from serum biochemistry.
Revista da Associacao Medica Brasileira (1992)
Sep 16, 2024
OBJECTIVE: The study used machine learning models to predict the clinical outcome with various attributes or when the models chose features based on their algorithms.
Machine learning to identify precachexia and cachexia: a multicenter, retrospective cohort study.
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Sep 3, 2024
BACKGROUND: Detection of precachexia is important for the prevention and treatment of cachexia. However, how to identify precachexia is still a challenge.
C-reactive protein (CRP) evaluation in human urine using optical sensor supported by machine learning.
Scientific reports
Aug 14, 2024
The rapid and sensitive indicator of inflammation in the human body is C-Reactive Protein (CRP). Determination of CRP level is important in medical diagnostics because, depending on that factor, it may indicate, e.g., the occurrence of inflammation o...
Predicting severity of acute appendicitis with machine learning methods: a simple and promising approach for clinicians.
BMC emergency medicine
Jun 18, 2024
BACKGROUNDS: Acute Appendicitis (AA) is one of the most common surgical emergencies worldwide. This study aims to investigate the predictive performances of 6 different Machine Learning (ML) algorithms for simple and complicated AA.
Development of an immunoinflammatory indicator-related dynamic nomogram based on machine learning for the prediction of intravenous immunoglobulin-resistant Kawasaki disease patients.
International immunopharmacology
May 3, 2024
BACKGROUND: Approximately 10-20% of Kawasaki disease (KD) patients suffer from intravenous immunoglobulin (IVIG) resistance, placing them at higher risk of developing coronary artery aneurysms. Therefore, we aimed to construct an IVIG resistance 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
Apr 18, 2024
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...
Blood-based biomarkers of chronic inflammation.
Expert review of molecular diagnostics
May 22, 2023
INTRODUCTION: Diseases related to chronic persisting inflammation are amongst the largest sources of morbidity and health costs, yet biomarkers for early diagnosis, prognosis, and treatment response are not sufficiently effective.
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