WGCNA selection of SIC disease-related modules co-expressed genes. by Wan-Jing Zhen (20427813)

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Experimental validation. by Wan-Jing Zhen (20427813)

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GO and KEGG analysis. by Wan-Jing Zhen (20427813)

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S3 Fig - by Wan-Jing Zhen (20427813)

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KEGG enrichment analysis. by Wan-Jing Zhen (20427813)

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GSEA results. by Wan-Jing Zhen (20427813)

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GO enrichment analysis. by Wan-Jing Zhen (20427813)

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Constructing Accurate Potential Energy Surfaces with Limited High-Level Data Using Atom-Centered Potentials and Density Functional Theory by Mahsa Nazemi-Ashani (21876936)

“…We present a general method for developing a Δ-DFT-type approach that enables the generation of energies with complete basis set CCSD­(T)-level accuracy on the potential energy surfaces (PESs) of molecules of arbitrary size, while requiring only a minimal set (hundreds) of high-level wave function theory reference data points for fitting. …”

Proportion of positive results in each algorithm and latent prevalences by age (a) and comorbidity (b) groups. by Jia Wei (120974)

Trace plots of estimated prevalence, sensitivity, and specificity of each algorithm of Model-3 in the primary analysis. by Jia Wei (120974)

Kaplan–Meier estimates of cumulative incidence for autism spectrum disorder by cumulative dose exposure level with 95% confidence intervals. by Emma N. Cleary (21103967)

Network visualization of OECD member and partner trade relations using the wCL GHAC community detection method. by Petr Prokop (19959315)

Schematic of the directed network flow entropy (DNFE) algorithm. by Xueqing Peng (10678527)

The spatial distribution of 5,230 in-situ soil samples used to develop a data-driven model of soil organic carbon as a percentage by mass in agricultural soil. by James R. Kellner (7846706)

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Calculation of composite scores using z-scores. by Yuanying Pang (19787125)

“…</p><p>Research design and method</p><p>Using machine learning algorithms including logistic regression, ridge regression, support vector machines, classification trees, and random forests, we predicted adherence from weeks 3 to 12. …”

<b>Exploring blood diagnostic markers for diabetic nephropathy through metabolomics and machine learning</b> by yuan sun (20399105)

Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived from the 3-level wavelet transform (WT) at four resolutions. These features were used as inputs for traditional ML algorithms. The left map demonstrates the correlation matrix of 52 features crafted from 4 resolutions of the 3-level WT, which are used as inputs for traditional ML algorithms.... by Quang Dung Dinh (20995766)

“…These features were used as inputs for traditional ML algorithms. The left map demonstrates the correlation matrix of 52 features crafted from 4 resolutions of the 3-level WT, which are used as inputs for traditional ML algorithms. …”

A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

“…The A* algorithm then evaluated connectivity by minimizing Euclidean distance and heuristic cost between cells. …”

Birkinshaw et al. 2024. Suitability of different machine learning algorithms for the classificationof the proportion of grassland-based forages at the herd level usingmid-infrared... by Amy Birkinshaw (19731610)

“…Suitability of different machine learning algorithms for the classification of the proportion of grassland-based forages at the herd level using mid-infrared spectral information from routine milk control</p>…”

Model-Based Clustering of Categorical Data Based on the Hamming Distance by Raffaele Argiento (647076)

“…<p>A model-based approach is developed for clustering categorical data with no natural ordering. The proposed method exploits the Hamming distance to define a family of probability mass functions to model the data. …”