Rohit Bakshi, M.D.

Co-Author

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This page shows the publications co-authored by Rohit Bakshi and Charles Guttmann.

Rohit Bakshi

Connection Strength

2.953

Charles Guttmann

Microstructural Changes in the Left Mesocorticolimbic Pathway are Associated with the Comorbid Development of Fatigue and Depression in Multiple Sclerosis. J Neuroimaging. 2021 05; 31(3):501-507.
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Score: 0.230
Characterizing Clinical and MRI Dissociation in Patients with Multiple Sclerosis. J Neuroimaging. 2017 09; 27(5):481-485.
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Score: 0.175
An expanded composite scale of MRI-defined disease severity in multiple sclerosis: MRDSS2. Neuroreport. 2014 Oct 01; 25(14):1156-61.
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Score: 0.148
Microstructural changes in the striatum and their impact on motor and neuropsychological performance in patients with multiple sclerosis. PLoS One. 2014; 9(7):e101199.
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Score: 0.146
Magnetic resonance disease severity scale (MRDSS) for patients with multiple sclerosis: a longitudinal study. J Neurol Sci. 2012 Apr 15; 315(1-2):49-54.
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Score: 0.122
Brain MRI lesion load at 1.5T and 3T versus clinical status in multiple sclerosis. J Neuroimaging. 2011 Apr; 21(2):e50-6.
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Score: 0.116
The relationship between normal cerebral perfusion patterns and white matter lesion distribution in 1,249 patients with multiple sclerosis. J Neuroimaging. 2012 Apr; 22(2):129-36.
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Score: 0.116
The relationships among MRI-defined spinal cord involvement, brain involvement, and disability in multiple sclerosis. J Neuroimaging. 2012 Apr; 22(2):122-8.
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Score: 0.116
One year activity on subtraction MRI predicts subsequent 4 year activity and progression in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2011 Oct; 82(10):1125-31.
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Score: 0.116
Identification and clinical impact of multiple sclerosis cortical lesions as assessed by routine 3T MR imaging. AJNR Am J Neuroradiol. 2011 Mar; 32(3):515-21.
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Score: 0.115
Regional white matter atrophy--based classification of multiple sclerosis in cross-sectional and longitudinal data. AJNR Am J Neuroradiol. 2009 Oct; 30(9):1731-9.
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Score: 0.104
Spinal cord lesions and clinical status in multiple sclerosis: A 1.5 T and 3 T MRI study. J Neurol Sci. 2009 Apr 15; 279(1-2):99-105.
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Score: 0.101
3 T MRI relaxometry detects T2 prolongation in the cerebral normal-appearing white matter in multiple sclerosis. Neuroimage. 2009 Jul 01; 46(3):633-41.
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Score: 0.101
Rate of brain atrophy in benign vs early multiple sclerosis. Arch Neurol. 2009 Feb; 66(2):234-7.
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Score: 0.100
Deep gray matter involvement on brain MRI scans is associated with clinical progression in multiple sclerosis. J Neuroimaging. 2009 Jan; 19(1):3-8.
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Score: 0.099
Unbiased treatment effect estimates by modeling the disease process of multiple sclerosis. J Neurol Sci. 2009 Mar 15; 278(1-2):54-9.
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Score: 0.099
Predicting clinical progression in multiple sclerosis with the magnetic resonance disease severity scale. Arch Neurol. 2008 Nov; 65(11):1449-53.
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Score: 0.098
MRI in multiple sclerosis: current status and future prospects. Lancet Neurol. 2008 Jul; 7(7):615-25.
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Score: 0.096
Medulla oblongata volume: a biomarker of spinal cord damage and disability in multiple sclerosis. AJNR Am J Neuroradiol. 2008 Sep; 29(8):1465-70.
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Score: 0.096
Segmentation of subtraction images for the measurement of lesion change in multiple sclerosis. AJNR Am J Neuroradiol. 2008 Feb; 29(2):340-6.
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Score: 0.093
Thalamic atrophy and cognition in multiple sclerosis. Neurology. 2007 Sep 18; 69(12):1213-23.
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Score: 0.091
Multiple sclerosis medical image analysis and information management. J Neuroimaging. 2005; 15(4 Suppl):103S-117S.
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Score: 0.075
MRI Lesion State Modulates the Relationship Between Serum Neurofilament Light and Age in Multiple Sclerosis. J Neuroimaging. 2021 03; 31(2):388-393.
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Score: 0.057
Temporal association of sNfL and gad-enhancing lesions in multiple sclerosis. Ann Clin Transl Neurol. 2020 06; 7(6):945-955.
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Score: 0.055
Dual-Sensitivity Multiple Sclerosis Lesion and CSF Segmentation for Multichannel 3T Brain MRI. J Neuroimaging. 2018 01; 28(1):36-47.
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Score: 0.046
The effect of alcohol and red wine consumption on clinical and MRI outcomes in multiple sclerosis. Mult Scler Relat Disord. 2017 Oct; 17:47-53.
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Score: 0.045
Exploration of machine learning techniques in predicting multiple sclerosis disease course. PLoS One. 2017; 12(4):e0174866.
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Score: 0.044
Handling changes in MRI acquisition parameters in modeling whole brain lesion volume and atrophy data in multiple sclerosis subjects: Comparison of linear mixed-effect models. Neuroimage Clin. 2015; 8:606-10.
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Score: 0.039
Using multiple imputation to efficiently correct cerebral MRI whole brain lesion and atrophy data in patients with multiple sclerosis. Neuroimage. 2015 Oct 01; 119:81-8.
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Score: 0.039
Smoking and disease progression in multiple sclerosis. Arch Neurol. 2009 Jul; 66(7):858-64.
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Score: 0.026
Incidence and factors associated with treatment failure in the CLIMB multiple sclerosis cohort study. J Neurol Sci. 2009 Sep 15; 284(1-2):116-9.
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Score: 0.025
Incorporating domain knowledge into the fuzzy connectedness framework: application to brain lesion volume estimation in multiple sclerosis. IEEE Trans Med Imaging. 2007 Dec; 26(12):1670-80.
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Score: 0.023

Connection Strength

The connection strength for co-authors is the sum of the scores for each of their shared publications.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.