Multivariate curve resolution (MCR) is a widespread methodology for the analysis of process data in many different application fields. This article intends to propose a critical review of the recently published works. Particular attention will be paid to situations requiring advanced and tailored applications of multivariate curve resolution, dealing with improvements in preprocessing methods, multi-set data arrangements, tailored constraints, issues related to non-ideal noise structure and deviation to linearity. These analytical issues are tackling the limits of applicability of MCR methods and, therefore, they can be considered as the most challenging ones.
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http://dx.doi.org/10.1016/j.aca.2012.12.028 | DOI Listing |
JMIR Med Inform
January 2025
Department of Endocrinology and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Background: Many tools have been developed to predict the risk of diabetes in a population without diabetes; however, these tools have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, and low sensitivity or specificity.
Objective: We aimed to develop and validate an easy, systematic index for predicting diabetes risk in the Asian population.
Methods: We collected the data from the NAGALA (NAfld [nonalcoholic fatty liver disease] in the Gifu Area, Longitudinal Analysis) database.
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 PDFBMC Pulm Med
January 2025
Department of Respiratory Medicine, Faculty of Life Sciences, Kumamoto University, Kumamoto 1-1-1 Honjo, Chuo-ku, 860-8556, Japan.
Background: Fibrotic types of interstitial lung abnormalities seen on high-resolution computed tomography scans, characterised by traction bronchiolectasis/bronchiectasis with or without honeycombing, are predictors of progression and poor prognostic factors of interstitial lung abnormalities. There are no reports on the clinical characteristics of fibrotic interstitial lung abnormalities on high-resolution computed tomography scans. Therefore, we aimed to examine these clinical characteristics and clarify the predictive factors of fibrotic interstitial lung abnormalities on high-resolution computed tomography scans.
View Article and Find Full Text PDFBMC Gastroenterol
January 2025
Department of Nephrology, QingPu Branch of Zhongshan Hospital Affiliated to Fudan University, Shanghai, People's Republic of China.
Background: Gallstone disease (GSD) is associated with obesity. The Cardiometabolic Index (CMI), a metric that accurately assesses central adiposity and visceral fat, has not been extensively studied in relation to GSD risk. This study investigates the link between CMI and GSD incidence in U.
View Article and Find Full Text PDFSci 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).
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