Results 141 to 150 of about 864,389 (286)
Background: This study aimed to fill a critical research gap by comparing traditional Structural Equation Modelling (SEM) with hybrid Bayesian-Machine Learning (ML) models in marketing research, focusing on the limited exploration of these advanced ...
Chacha Magasi
doaj +1 more source
Bayesian models for aggregate and individual patient data component network meta-analysis. [PDF]
Efthimiou O +7 more
europepmc +1 more source
Machine‐Learning Microfluidic Minute‐Scale Microorganism Metrics Monitoring(M6)
ABSTRACT On‐site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion, particularly for aerosol‐transmitted pathogens. Here, we report a rapid detection platform that integrates a Puri‐focusing microfluidic chip, electrochemical impedance spectroscopy (EIS), and ...
Ning Yang +14 more
wiley +1 more source
Spatio-Temporal Bayesian Models for Malaria Risk Using Survey and Health Facility Routine Data in Rwanda. [PDF]
Semakula M, Niragire F, Faes C.
europepmc +1 more source
Oligonucleotide‐based fluorescence in situ hybridization probes were developed in the model citrus species Citrus maxima. These probes were applied to comparative karyotyping across 14 species in the Rutaceae family. This analysis revealed chromosomal evolution in lineages that diverged from Citrus nearly 52 million years ago.
Li He +9 more
wiley +1 more source
Stochastic approximation cut algorithm for inference in modularized Bayesian models. [PDF]
Liu Y, Goudie RJB.
europepmc +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Analysing pneumococcal invasiveness using Bayesian models of pathogen progression rates. [PDF]
Løchen A, Truscott JE, Croucher NJ.
europepmc +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Hierarchical Bayesian models of transcriptional and translational regulation processes with delays. [PDF]
Cortez MJ +4 more
europepmc +1 more source

