Preliminary search for price decreases for the period 01 Jan. 2021–14 Jun. 2022. by Jevgeni Tarassov (13889285)

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)

The fraction of predicted heterozygotes that are set to “No Call” by RHA decreases as the size of the heterozygote cluster increases. by Orna Mizrahi-Man (42539)

Average stiffness for the force range of 50–100 N. by Jihun Kim (10091)

AIM-100 reduces dsRNA silencing in body wall muscle and decreases DA neurodegeneration. by Anthony L. Gaeta (13272609)

Comparison of baseline characteristics stratified by the occurrence of ISR > 50%. by Jae-Chan Ryu (2850581)

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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)

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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)

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Evaluation index results for the JS-10 phantom. by Masakazu Tsujimoto (22339504)

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NEMA IEC body phantom. by Masakazu Tsujimoto (22339504)

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Relationship between contrast, noise, and CNR. by Masakazu Tsujimoto (22339504)

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JS-10 phantom. by Masakazu Tsujimoto (22339504)

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The raw data used for the analyses in this study. by Masakazu Tsujimoto (22339504)

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Binary and ordinal logistic regression analysis of predictors for the occurrence of ISR > 50%. by Jae-Chan Ryu (2850581)

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Means for STEM competence for pre- and post-test. by Esther Kim (2996622)

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Probability of release is decreased by hydrophobic mutations. by Matthew R. Bowers (8423115)

Means for global competence pre- and post-test scores. by Esther Kim (2996622)

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The PRAME-AS knockout cells showed a decrease in migration, proliferation, stemness, and viability. by Zahra Hosseininia (22265113)

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)

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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)

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