GWAS analysis using Cluster 2 data (shown in S1 Fig). by Ke Li (106849)

GWAS analysis using only Cluster 1 data (shown in S1 Fig). by Ke Li (106849)

GWAS analysis using Cluster 3 data (shown in S1 Fig). by Ke Li (106849)

GWAS analysis using Cluster 4 data (shown in S1 Fig). by Ke Li (106849)

GWAS analysis identifies several single nucleotide polymorphisms (SNPs) that are associated with the changes in viral copies. by Ke Li (106849)

GWAS analysis identifies several single nucleotide polymorphisms (SNPs) that are associated with the changes in viral copies. by Ke Li (106849)

Top predictive variables for KDIGO stage ≥ 3 identified by the final Random Forest model. by Julian Müller-Kühnle (22265248)

The performance of eigenvectors of the covariance matrix in a model with more complex population structure. by Joshua G. Schraiber (8027060)

Correlation in site-level DNA methylation estimates between TMS and RRBS data after permutation. by Amy Longtin (21409957)

Predictors in ordinal regression model for GDS. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Classification of hand grip strength. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Rating scale for functional severity [28]. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Regression model coefficients. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

ICOPE screening positive participant’s responses. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

WHO BMI classification for adults. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Performance comparison of ML models. by Gourab Saha (8987405)

“…<div><p>As the world population is increasing day by day, so is the need for more advanced automated precision agriculture to meet the increasing demands for food while decreasing labor work and saving water for crops. …”

Comparative data of different soil samples. by Gourab Saha (8987405)

“…<div><p>As the world population is increasing day by day, so is the need for more advanced automated precision agriculture to meet the increasing demands for food while decreasing labor work and saving water for crops. …”

Confusion matrix of random forest model. by Gourab Saha (8987405)

“…<div><p>As the world population is increasing day by day, so is the need for more advanced automated precision agriculture to meet the increasing demands for food while decreasing labor work and saving water for crops. …”

Sensor value scenario for fuzzy logic algorithm. by Gourab Saha (8987405)

“…<div><p>As the world population is increasing day by day, so is the need for more advanced automated precision agriculture to meet the increasing demands for food while decreasing labor work and saving water for crops. …”

Evaluation metrics of selected ML models. by Gourab Saha (8987405)

“…<div><p>As the world population is increasing day by day, so is the need for more advanced automated precision agriculture to meet the increasing demands for food while decreasing labor work and saving water for crops. …”