We counted numbers of unique pLoF, missense, and synonymous variants in UKB in each quintile of the coding sequence (CDS) of all protein-coding genes and clustered the variants using Gaussian mixture models. We limited the analyses to genes with 鈮 5 variants of each type (16,473 genes)...
When parental education was considered as the exposure, the magnitude of indirect effects was in the same direction and slightly lower than that reported in main analysis (see FigureS4). Furthermore, the Bayesian scoring procedure supported a pattern of models similar to the one found for parental...
To evaluate the optimal number of clusters that can best describe both the empirical weight distributions as well as the simulated neuronal responses, Dirichlet process with Gaussian mixture modelling58and time-series K-Means analysis81were performed using the scikit-learn82and tslearn59Python machine ...
Microalgae classification using semi-supervised and active learning based on Gaussian mixture models Microalgae are unicellular organisms that have different shapes, sizes and structures. Classifying these microalgae manually can be an expensive task, beca... P Drews,RG Colares,P Machado,... - 《Jour...
“information integration” was negligible: − 0.19 [− 0.61 0.31]. What is more, the indirect effect from “sensory capability” onto cognitive status (not shown in Fig.6G) was insubstantial: 0.13 [− 0.22 0.47]. When comparing the reduced models on the basis of the posterior ...
From this perspective, the LBM strategy proposed in this work, and its future developments, will help to better understand these processes and to quantify the uncertainties hidden in the assumptions of the theoretical models. Methods The Lattice Boltzmann method On a macroscopic level, a fluid is ...
The lack of interpretability in artificial intelligence models (i.e., deep learning, machine learning, and rules-based) is an obstacle to their widespread adoption in the healthcare domain. The absence of understandability and transparency frequently leads to (i) inadequate accountability and (ii) ...
The lack of interpretability in artificial intelligence models (i.e., deep learning, machine learning, and rules-based) is an obstacle to their widespread adoption in the healthcare domain. The absence of understandability and transparency frequently lea