 Connection
Andrew Smith to Adipose Tissue
This is a "connection" page, showing publications Andrew Smith has written about Adipose Tissue.
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Connection Strength |
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1.852 |
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Smith AC, Albin SR, Abbott R, Crawford RJ, Hoggarth MA, Wasielewski M, Elliott JM. Confirming the geography of fatty infiltration in the deep cervical extensor muscles in whiplash recovery. Sci Rep. 2020 07 10; 10(1):11471.
Score: 0.546
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Smith AC, Knikou M, Yelick KL, Alexander AR, Murnane MM, Kritselis AA, Houmpavlis PJ, McPherson JG, Wasielewski M, Hoggarth MA, Elliott JM. MRI measures of fat infiltration in the lower extremities following motor incomplete spinal cord injury: reliability and potential implications for muscle activation. Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug; 2016:5451-5456.
Score: 0.416
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Smith AC, Parrish TB, Abbott R, Hoggarth MA, Mendoza K, Chen YF, Elliott JM. Muscle-fat MRI: 1.5 Tesla and 3.0 Tesla versus histology. Muscle Nerve. 2014 Aug; 50(2):170-6.
Score: 0.361
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Weber KA, Abbott R, Bojilov V, Smith AC, Wasielewski M, Hastie TJ, Parrish TB, Mackey S, Elliott JM. Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions. Sci Rep. 2021 08 16; 11(1):16567.
Score: 0.147
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Elliott JM, Smith AC, Hoggarth MA, Albin SR, Weber KA, Haager M, Fundaun J, Wasielewski M, Courtney DM, Parrish TB. Muscle fat infiltration following whiplash: A computed tomography and magnetic resonance imaging comparison. PLoS One. 2020; 15(6):e0234061.
Score: 0.136
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Weber KA, Smith AC, Wasielewski M, Eghtesad K, Upadhyayula PA, Wintermark M, Hastie TJ, Parrish TB, Mackey S, Elliott JM. Deep Learning Convolutional Neural Networks for the Automatic?Quantification of?Muscle Fat Infiltration Following Whiplash Injury. Sci Rep. 2019 05 28; 9(1):7973.
Score: 0.126
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Cloney M, Smith AC, Coffey T, Paliwal M, Dhaher Y, Parrish T, Elliott J, Smith ZA. Fatty infiltration of the cervical multifidus musculature and their clinical correlates in spondylotic myelopathy. J Clin Neurosci. 2018 Nov; 57:208-213.
Score: 0.120
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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