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Versus Stem sentence examples within mean diagnostic accuracy
Findings The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
Findings The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
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The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and the mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and the mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
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Versus Stem sentence examples within Leaf Versus Stem
Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ.
Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ.
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Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ.
Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ.
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Versus Stem sentence examples within Tt Versus Stem
Findings The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
Findings The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
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The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and the mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and the mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
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Versus Stem sentence examples within versus stem cell
It would be ironic if viruses turn out to be a useful tool and an ideal means in our quest to verify a genetic versus stem cell origin of cancer.
It would be ironic if viruses turn out to be a useful tool and an ideal means in our quest to verify a genetic versus stem cell origin of cancer.
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disease versus normal, differentiated cells versus stem cells or gene knockdown cells versus wild-type cells) m6A-mediated functional genes.
disease versus normal, differentiated cells versus stem cells or gene knockdown cells versus wild-type cells) m6A-mediated functional genes.
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10.3390/molecules26040842
Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ.
Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ.
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10.20944/PREPRINTS202101.0181.V2
Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ.
Depending on the Miscanthus genotype, season, and harvest time as well as plant component (leaf versus stem), correlations between structure and properties of the corresponding isolated lignins differ.
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10.1161/JAHA.119.017290
The relative 30-day mortality risk for TS versus STEMI and NSTEMI was higher for smokers than nonsmokers (adjusted P interaction STEMI=0.
The relative 30-day mortality risk for TS versus STEMI and NSTEMI was higher for smokers than nonsmokers (adjusted P interaction STEMI=0.
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10.1163/23641177-BJA10022
Since subject-integrated learning has already been conducted in Japan, we consider the further discussion required regarding specific objective of STEAM versus STEM education.
Since subject-integrated learning has already been conducted in Japan, we consider the further discussion required regarding specific objective of STEAM versus STEM education.
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10.1016/j.eclinm.2021.101115
Findings The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
Findings The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
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10.1016/j.xrrt.2021.07.003
Therefore, the goal of this study was to identify if surgeons change their subscapularis takedown preference when performing stemless versus stemmed TSA.
Therefore, the goal of this study was to identify if surgeons change their subscapularis takedown preference when performing stemless versus stemmed TSA.
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10.3390/cancers13112738
It would be ironic if viruses turn out to be a useful tool and an ideal means in our quest to verify a genetic versus stem cell origin of cancer.
It would be ironic if viruses turn out to be a useful tool and an ideal means in our quest to verify a genetic versus stem cell origin of cancer.
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10.2139/ssrn.3857645
The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and the mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
The DCNN (2D SCI), DCNN (2D MCI), DCNN(2D+t), and RNN models established based on UI dataset for TTS versus STEMI prediction showed mean diagnostic accuracy 73%, 75%, 80%, and 75% respectively, and the mean diagnostic accuracy of 74%, 74%, 77%, and 73%, respectively, on the external validation.
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10.1093/bioinformatics/btz316
disease versus normal, differentiated cells versus stem cells or gene knockdown cells versus wild-type cells) m6A-mediated functional genes.
disease versus normal, differentiated cells versus stem cells or gene knockdown cells versus wild-type cells) m6A-mediated functional genes.
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10.1158/1538-7445.SABCS18-P5-05-06
proliferation versus stem-like expansion) in luminal breast cancer models.
proliferation versus stem-like expansion) in luminal breast cancer models.
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10.20944/preprints201911.0170.v1
Ongoing therapeutic developments for PI3Kassociated cancers may therefore benefit from a better understanding of the pathway’s two-layered and highly context-dependent regulation of cell growth versus stemness.
Ongoing therapeutic developments for PI3Kassociated cancers may therefore benefit from a better understanding of the pathway’s two-layered and highly context-dependent regulation of cell growth versus stemness.
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10.1111/AEC.12678
We tested the predictions that SLA and stem diameter growth rate would be positively correlated in saplings but unrelated in adults while, in both age classes, faster‐GR species would have higher light‐saturated photosynthetic rate (Asat), higher leaf nutrient concentrations, higher branch‐scale biomass allocation to leaf versus stem tissues and lower wood density (WD).
We tested the predictions that SLA and stem diameter growth rate would be positively correlated in saplings but unrelated in adults while, in both age classes, faster‐GR species would have higher light‐saturated photosynthetic rate (Asat), higher leaf nutrient concentrations, higher branch‐scale biomass allocation to leaf versus stem tissues and lower wood density (WD).
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10.1104/pp.19.00524
Using deep learning, we classified lamina versus stems with 97.
Using deep learning, we classified lamina versus stems with 97.
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10.3760/cma.j.issn.0253-3758.2019.03.006
Conclusions: In patients with AMI, the constituent ratio of NSTEMI versus STEMI is increased during the 11 years.
Conclusions: In patients with AMI, the constituent ratio of NSTEMI versus STEMI is increased during the 11 years.
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10.1002/14651858.CD013201.PUB2
SELECTION CRITERIA
We attempted to identify randomised controlled trials, quasi-randomised controlled trials, and cluster trials comparing (1) stem cell-based interventions versus control; (2) mesenchymal stromal cells (MSCs) of type or source versus MSCs of other type or source; (3) stem cell-based interventions other than MSCs of type or source versus stem cell-based interventions other than MSCs of other type or source; or (4) MSCs versus stem cell-based interventions other than MSCs.
SELECTION CRITERIA
We attempted to identify randomised controlled trials, quasi-randomised controlled trials, and cluster trials comparing (1) stem cell-based interventions versus control; (2) mesenchymal stromal cells (MSCs) of type or source versus MSCs of other type or source; (3) stem cell-based interventions other than MSCs of type or source versus stem cell-based interventions other than MSCs of other type or source; or (4) MSCs versus stem cell-based interventions other than MSCs.
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10.1111/nph.16287
We tested the effect of climate versus stem length on vessel diameter in two tree species (Embothrium coccineum, Nothofagus antarctica) that both span an exceptionally wide precipitation gradient (2,300-500 mm).
We tested the effect of climate versus stem length on vessel diameter in two tree species (Embothrium coccineum, Nothofagus antarctica) that both span an exceptionally wide precipitation gradient (2,300-500 mm).
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