Variable importance plot (mean decrease accuracy and mean decrease Gini). by Fernando Martinez-Taboada (8655132)

Mean of the difference between the RV-GLS value of the expert and trainees in four consecutive groups of 25 fetal heart clips. by Chantelle M. de Vet (16535257)

Mean of the difference between the LV-GLS value of the expert and trainees in four consecutive groups of 25 fetal heart clips. by Chantelle M. de Vet (16535257)

Detailed meta–analyses in untreated hypothyroid patients compared with controls for each HRV parameters: RR intervals, SDNN, RMSSD, pNN50, TP, LF, HF, LF/HF. by Valentin Brusseau (12769704)

Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 12 covariates chosen using subjective feature selection. by Dennis Ochola (11626912)

Subjects:

Predictions of random forests (RF), gradient boosting machines (GBM), and neural networks (NN) trained on 17 covariates selected after recursive feature selection. by Dennis Ochola (11626912)

Subjects:

Prevalence and incidence rates per 100,000 individuals with de novo AML. by Hyun Jin Han (18592254)

Germ cell size decreases before corpse formation. by Tea Kohlbrenner (19476160)

JBPOS0101 decreased Amyloid Beta (Aβ) aggregates in the cortex and hippocampal regions in 5xFAD mouse brains. by Jihoon Jeong (4852690)

S1 File - by Chantelle M. de Vet (16535257)

“…The student’s RV-GLS consistency was poor during the first 25 measurements, moderate-to good during the second 25 measurements and again poor-to-moderate during the final 50 measurements. Repeated measurements analysis showed a significant decrease in variability of the LV- and RV-GLS score differences between the expert and trainees over time (<i>p</i>_adj<0.001), which was not significantly different between trainees. …”

GLS analysis with 2D-STE software. by Chantelle M. de Vet (16535257)

“…The student’s RV-GLS consistency was poor during the first 25 measurements, moderate-to good during the second 25 measurements and again poor-to-moderate during the final 50 measurements. Repeated measurements analysis showed a significant decrease in variability of the LV- and RV-GLS score differences between the expert and trainees over time (<i>p</i>_adj<0.001), which was not significantly different between trainees. …”

Comparison of mean differences in temperature decreases. by Hans-Jörg Gillmann (8460585)

Characteristics of patient with de novo AML in South Korea from 2011 to 2020. by Hyun Jin Han (18592254)

Numbers of all fractures, arranged in order of decreasing mean age and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age. by Camilla Bergh (9904522)

“…<p>Numbers of all fractures, arranged in order of decreasing mean age and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age.…”

Age-specific incidence rate of de novo AML from 2011 to 2019 in Korea. by Hyun Jin Han (18592254)

Age-specific prevalence cases of de novo AML from 2011 to 2019 in Korea. by Hyun Jin Han (18592254)

Expression of ApoB-50 decreased lipid accumulation and inhibited HCV production. by Bei Wang (116772)

The energy, the total number of proteins, fat, and carbohydrates of the diets per 100 g. by Fatima Dikhanbayeva (11501962)

Numbers of all fractures occurring in men, arranged in order of decreasing mean age, and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age. by Camilla Bergh (9904522)

“…<p>Numbers of all fractures occurring in men, arranged in order of decreasing mean age, and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age.…”

Numbers of all fractures occurring in women, arranged in order of decreasing mean age, and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age. by Camilla Bergh (9904522)

“…<p>Numbers of all fractures occurring in women, arranged in order of decreasing mean age, and with proportion of each of the fracture types in patients over 50, 65, and 75 years of age.…”