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Derivation and validation of a clinical predictive model for longer duration diarrhea among pediatric patients in Kenya using machine learning algorithms.
BMC Med Inform Decis Mak
January 2025
Kenya Medical Research Institute- Center for Global Health Research (KEMRI-CGHR), P.O Box 1578-40100, Kisumu, Kenya.
Background: Despite the adverse health outcomes associated with longer duration diarrhea (LDD), there are currently no clinical decision tools for timely identification and better management of children with increased risk. This study utilizes machine learning (ML) to derive and validate a predictive model for LDD among children presenting with diarrhea to health facilities.
Methods: LDD was defined as a diarrhea episode lasting ≥ 7 days.
Reconfigured single- and double-diode models for improved modelling of solar cells/modules.
Sci Rep
January 2025
Department of Computer Engineering, College of Computer and Information Sciences, Majmaah University, Majmaah, 11952, Saudi Arabia.
Proper modeling of PV cells/modules through parameter identification based on the real current-voltage (I-V) data is important for the efficiency of PV systems. Most related works have concentrated on the classical single-diode model (SDM) and double-diode model (DDM) and their parameter extraction by various metaheuristic algorithms. In order to render more accurate and representative modeling, this paper adds a small resistance in series with the diodes in SDM and DDM.
View Article and Find Full Text PDFHigh-resolution anorectal manometry (HR-ARM) is the gold standard for anorectal functional disorders' evaluation, despite being limited by its accessibility and complex data analysis. The London Protocol and Classification were developed to standardize anorectal motility patterns classification. This proof-of-concept study aims to develop and validate an artificial intelligence model for identification and differentiation of disorders of anal tone and contractility in HR-ARM.
View Article and Find Full Text PDFTwo-Phase Extraction for Comprehensive Analysis of the Plant Metabolome by NMR.
Methods Mol Biol
January 2025
Grupo Metabolômica, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, RJ, Brazil.
Metabolomics is the area of research, which strives to obtain complete metabolic fingerprints, to detect differences between them and to provide hypothesis to explain those differences (Schripsema J, Dagnino D, Handbook of chemical and biological plant analytical methods. Wiley, New York, 2015). However, obtaining complete metabolic fingerprints is not an easy task.
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