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Luo M, Anees SA, Huang Q, Qin X, Qin Z, Fan J, Han G, Zhang L, Shafri HZM (2024) Improving forest above-ground biomass estimation by integrating individual machine learning models. Forests 15(6):975. https://doi.org/10.3390/f15060975 Article Google Scholar Maddu R, Vanga AR, Sa...
With this, we created Single Cell pIpeline PredIctiOn (SCIPIO-86), the first dataset of single-cell pipeline performance. We then developed a set of supervised machine learning models to predict the performance of a given pipeline on a given dataset using a combination of pipeline and dataset ...
of environmental parameters in explaining offspring survival given the reefs of their parental stock (Fig.3a, b). These “intrinsic resistance models”, represented as polynomial equations (Fig.4a–d), therefore provide the framework for the identification of locations where corals with high heat ...
The classification accuracy ranged from 0.993 (Random Forest) to 0.998 (Neural Networks). Over the four models, only 11 examples were misclassified, especially those belonging to the minority class (Archaea). From variable importance, tRNA topological and Shannon’s entropy, nucleotide frequencies in...
of these models suggested that ERK dynamics throughout the cell cycle, rather than immediately after growth factor stimulation, were associated with the likelihood of cell division. Overall, this work contributes insights into the predictive power of intra-cellular signaling dynamics for cell fate ...
The complete contours of the forest and fruit wood borer galleries are extracted from the input single 2D images of the forest and fruit wood borer galleries, and the sketch-based reconstruction method is applied to generate 3D models. In particular, during the model’s expansion, its expansion...
Thus, the need to expand the knowledge on potential predictors and models that can help predict AMD phenotypes evolving into late stages. Regarding imaging biomarkers, the use of optical coherence tomography (OCT)-based features seems to present several technical and practical advantages. Beyond its ...
Model.fit is the predictive accuracy (ccr) of each RF model developed. Models with four or more predictors (i.e., models 1-7, and 12) produced perfect fits to the data (Table 11.2). The models with three or less predictors (i.e., models 8-11) made good fits to the data, with...
as continuous gust modelling, discrete gust modelling, and computational fluid dynamics (CFD) [4]. Continuous gust modelling simulates smooth variations in wind gust behaviour using a continuous probability distribution [3]. The Dryden model is one of the most widely utilized models in this context...