Performance of the ceRNAR package using synthetic data with randomly selected correlation values from 0.8 to 0.9. by Yi-Wen Hsiao (13767916)

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with randomly selected correlation values from 0.3 to 0.9. by Yi-Wen Hsiao (13767916)

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with randomly selected correlation values from 0.5 to 0.7. by Yi-Wen Hsiao (13767916)

Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with randomly selected correlation values from 0.3 to 0.4. by Yi-Wen Hsiao (13767916)

The workflow of SCARS-Logistic algorithm. by Maryam Sadiq (7046903)

The scheme of CARS-Logistic algorithm. by Maryam Sadiq (7046903)

Smaller gene set of DFC was selected by a unique selection criterion. by Takeru Fujii (11731550)

The basic concept of our idea is illustrated graphically. by Yi-Wen Hsiao (13767916)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

Bayesian variable selection in distributed lag models: a focus on binary quantile and count data regressions by Daniel Dempsey (11805621)

Modeling Pregnancy Outcomes Through Sequentially Nested Regression Models by Xuan Bi (3096897)

“…Our approach explicitly bridges the connections across nested outcomes through computationally easy algorithms and enjoys theoretical guarantee of estimation and variable selection. …”

An Extension of the Unified Skew-Normal Family of Distributions and its Application to Bayesian Binary Regression by Paolo Onorati (20461248)

“…For more general prior distributions, the proposed methodology is based on a simple Gibbs sampler algorithm. We also claim that, in the <math><mrow><mi>p</mi><mo>></mo><mi>n</mi></mrow></math> case, our proposal presents better performances—both in terms of mixing and accuracy—compared to the existing methods.…”

Causal Inference Under Outcome-Based Sampling with Monotonicity Assumptions by Sung Jae Jun (17309092)

Parameter settings. by Yang Cao (53545)

“…Finally, the paper incorporates the sampling concept of elite individuals from the Estimation of Distribution Algorithm (EDA) to regenerate new solutions through the selection process in DE. …”

Flowchart scheme of the ML-based model. by Noshaba Qasmi (20405009)

Illustration of the workflow combining BayesFlow with missing data encoding. by Zijian Wang (481291)

Table_1_Prediction of spherical equivalent difference before and after cycloplegia in school-age children with machine learning algorithms.DOCX by Bei Du (12545461)

“…Random cluster sampling was used to select 2,467 students aged 6–18 years. …”

Table 1_Provider fidelity in tuberculosis screening practices among adolescents and adults living with HIV in public health facilities in Tanzania: a cross-sectional evaluation.doc... by Lucas L. Shilugu (22644302)

“…Simple random and systematic sampling methods were employed to select the records and sessions, respectively. …”

Table 2_Provider fidelity in tuberculosis screening practices among adolescents and adults living with HIV in public health facilities in Tanzania: a cross-sectional evaluation.doc... by Lucas L. Shilugu (22644302)

“…Simple random and systematic sampling methods were employed to select the records and sessions, respectively. …”

Supplementary file 1_Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery.docx by Veera Narayana Balabathina (22518524)

“…Dimensionality-reduction techniques (Principal Component Analysis—PCA and Minimum Noise Fraction—MNF) and band-selection strategies based on the Average Pairwise Absolute Difference (APAD) metric and species-specific band-ratio indices were implemented to mitigate spectral redundancy. …”