CFTR2.org Variants of Unknown Significance (VUS). by Eli Fritz McDonald (7382066)

Heart Rate-Based Intensity Monitoring During Interval Exercise. by Murat Kasap (827763)

The confusion matrix-based error rates analysis for fault detection. by Iqra Akhtar (19500587)

GO and KEGG enrichment results of significantly up-regulated gene sets. by Xiaoxiao Shi (109071)

Graphic representations, based on the means of all female and male faces from the Oslo Face Database, of the spatial frequencies significantly correlated with the normative ratings of attractiveness. by Morten Øvervoll (8298948)

“…<p>Graphic representations, based on the means of all female and male faces from the Oslo Face Database, of the spatial frequencies significantly correlated with the normative ratings of attractiveness.…”

Occurrence rate of eye contact. by Atsushi Nakazawa (15892700)

Subjects:

Subgroup analysis of ICU Stay based on pump type. by Mohamed R. Abdelraouf (21501468)

“…The analysis showed that pulsatile perfusion led to a significant decrease in creatinine level [MD = −0.14, 95% CI (−0.24, −.04), P < 0.004], lactate level [MD = −8.21, 95% CI (−13.16, −3.25), P < 0.001], hospital stay [MD = −1.38, 95% CI (−2.51, −0.25), P = 0.016], ICU stay [MD = −0.47, 95% CI (−0.82, −0.13), P = 0.007], intubation time [MD = −3.73, 95% CI (−5.42, −2.04), P < 0.001], and increase in creatinine clearance [MD = 10.08, 95% CI (3.36, 16.80), P < 0.003]. …”

Subgroup analysis of eGFR based on pump type. by Mohamed R. Abdelraouf (21501468)

“…The analysis showed that pulsatile perfusion led to a significant decrease in creatinine level [MD = −0.14, 95% CI (−0.24, −.04), P < 0.004], lactate level [MD = −8.21, 95% CI (−13.16, −3.25), P < 0.001], hospital stay [MD = −1.38, 95% CI (−2.51, −0.25), P = 0.016], ICU stay [MD = −0.47, 95% CI (−0.82, −0.13), P = 0.007], intubation time [MD = −3.73, 95% CI (−5.42, −2.04), P < 0.001], and increase in creatinine clearance [MD = 10.08, 95% CI (3.36, 16.80), P < 0.003]. …”

Results table of sales growth rate and customer satisfaction growth rate of each model algorithm. by Xing Tang (270198)

Subjects:

Significantly differentially abundant microbial taxa at the genus level. by Yoshiaki Sato (2170141)

Rate (times per hour) of frequency-based behaviors by Timepoint. by Yuke Wang (378692)

Subjects:

Frequency bands that show significant difference based on Shannon entropy and statistical moments of the distribution of information rate.... by Heng Jie Choong (21866796)

“…<p>Frequency bands that show significant difference based on Shannon entropy and statistical moments of the distribution of information rate. …”

Frequency bands that show significant difference based on Shannon entropy and statistical moments of the distribution of information rate.... by Heng Jie Choong (21866796)

“…<p>Frequency bands that show significant difference based on Shannon entropy and statistical moments of the distribution of information rate. …”

Non-normalized and normalized spatiotemporal parameters between age groups. by Markéta Rygelová (15453112)

There was no significant difference in knockdown rate between the <i>Serratia oryzae</i> enrichment and control groups within 60mins. by Haiyang Wang (22389)

Subjects:

Significant variables of DR association from univariate analyses. by Radhika Krishnan (15213756)

Top 1% significant features of GDZY dataset. by Jun Tan (46388)

Risk of fracture with competing risk in denosumab users versus non-users. by Arisa Kobayashi (4379608)

Significant differences between clusters on importance. by Padraic Rocliffe (16436723)

Significant differences between clusters on modifiability. by Padraic Rocliffe (16436723)