Quantitative analysis of natural gas depends on the calibration of a gas chromatograph with certified gas mixtures and the determination of a response relationship for each species by regression analysis. The uncertainty in this calibration is dominated by variations in the amount of the sample used for each analysis that are strongly correlated for all species measured in the same run. The "harmonisation" method described here minimises the influence of these correlations on the calculated calibration curves and leads to a reduction in the root-mean-square residual deviations from the fitted curve of a factor between 2 and 5. Consequently, it removes the requirement for each run in the calibration procedure to be carried out under the same external conditions, and opens the possibility that new data, measured under different environmental or instrumental conditions, can be appended to an existing calibration database.
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http://dx.doi.org/10.1016/j.chroma.2004.11.031 | DOI Listing |
J Cardiothorac Surg
January 2025
Department of Cardiology, The first Affiliated Hospital of Wannan, Medical College, Wuhu, China.
Background: He's team have recently developed a new Coronary Artery Tree description and Lesion EvaluaTion (CatLet) angiographic scoring system, which is capable of accounting for the variability in coronary anatomy, and risk-stratifying patients with coronary artery disease. Preliminary studies have demonstrated its superiority over the the Synergy between percutaneous coronary intervention with Taxus and Cardiac Surgery (SYNTAX) score with respect to outcome predictions for acute myocardial infarction (AMI) patients. However, there are fewer studies on the prognostic in chronic coronary artery disease(CAD).
View Article and Find Full Text PDFJ Racial Ethn Health Disparities
January 2025
Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Context: To evaluate algorithmic fairness in low birthweight predictive models.
Study Design: This study analyzed insurance claims (n = 9,990,990; 2013-2021) linked with birth certificates (n = 173,035; 2014-2021) from the Arkansas All Payers Claims Database (APCD).
Methods: Low birthweight (< 2500 g) predictive models included four approaches (logistic, elastic net, linear discriminate analysis, and gradient boosting machines [GMB]) with and without racial/ethnic information.
Sci Rep
January 2025
Center of Health Administration and Development Studies, Hubei University of Medicine, Shiyan, China.
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder, and critically ill patients with T2DM in intensive care unit (ICU) have an increased risk of mortality. In this study, we investigated the relationship between nine inflammatory indicators and prognosis in critically ill patients with T2DM to provide a clinical reference for assessing the prognosis of patients admitted to the ICU. Critically ill patients with T2DM were extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and divided into training and testing sets (7:3 ratio).
View Article and Find Full Text PDFUltrasound Med Biol
January 2025
Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, China; Fuzhou University Affiliated Provincial Hospital, Department of Ultrasound, Fuzhou, Fujian Province, China. Electronic address:
Objective: This study aimed to develop and validate a diagnostic model for gouty arthritis by integrating ultrasonographic radiomic features with clinical parameters.
Methods: A total of 604 patients suspected of having gouty arthritis were enrolled and randomly divided into a training set (n = 483) and a validation set (n = 121) in a 4:1 ratio. Univariate and multivariate analyses were conducted on the clinical data to identify statistically significant clinical features for constructing an initial diagnostic model.
Eur J Intern Med
January 2025
Istituti Clinici Scientifici Maugeri, IRCCS, Institute of Bari, Bari, Italy.
Background: Assessing the relative performance of machine learning (ML) methods and conventional statistical methods in predicting prognosis in heart failure (HF) still remains a challenging research field.
Methods: The primary outcome was three-year mortality. The following 5 machine learning approaches were used for modeling: Random Forest (RF), Gradient Boosting, Extreme Gradient Boosting (XGBoost), Support Vector Machine, and Multilayer perceptron.
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