April 2024
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27 Reads
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April 2024
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27 Reads
April 2024
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20 Reads
April 2024
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25 Reads
April 2023
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17 Reads
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1 Citation
April 2023
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34 Reads
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1 Citation
April 2023
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19 Reads
April 2022
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35 Reads
April 2022
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16 Reads
April 2022
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40 Reads
December 2021
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78 Reads
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8 Citations
Neurorehabilitation and Neural Repair
Objective Patients show substantial differences in response to rehabilitation therapy after stroke. We hypothesized that specific genetic profiles might explain some of this variance and, secondarily, that genetic factors are related to cerebral atrophy post-stroke. Methods The phase 3 ICARE study examined response to motor rehabilitation therapies. In 216 ICARE enrollees, DNA was analyzed for presence of the BDNF val ⁶⁶ met and the ApoE ε4 polymorphism. The relationship of polymorphism status to 12-month change in motor status (Wolf Motor Function Test, WMFT) was examined. Neuroimaging data were also evaluated (n=127). Results Subjects were 61±13 years old (mean±SD) and enrolled 43±22 days post-stroke; 19.7% were BDNF val ⁶⁶ met carriers and 29.8% ApoE ε4 carriers. Carrier status for each polymorphism was not associated with WMFT, either at baseline or over 12 months of follow-up. Neuroimaging, acquired 5±11 days post-stroke, showed that BDNF val ⁶⁶ met polymorphism carriers had a 1.34-greater degree of cerebral atrophy compared to non-carriers (P=.01). Post hoc analysis found that age of stroke onset was 4.6 years younger in subjects with the ApoE ε4 polymorphism (P=.02). Conclusion Neither the val ⁶⁶ met BDNF nor ApoE ε4 polymorphism explained inter-subject differences in response to rehabilitation therapy. The BDNF val ⁶⁶ met polymorphism was associated with cerebral atrophy at baseline, echoing findings in healthy subjects, and suggesting an endophenotype. The ApoE ε4 polymorphism was associated with younger age at stroke onset, echoing findings in Alzheimer’s disease and suggesting a common biology. Genetic associations provide insights useful to understanding the biology of outcomes after stroke.
... Individuals with Met alleles also had greater cerebral atrophy on MRI. 62 Sensitivity analysis included an additional meta-analysis being conducted with data from 5 studies included in this analysis. The only excluded 59 study provided no details on whether and if so, how many sessions of any form of rehabilitation were provided to the participants. ...
December 2021
Neurorehabilitation and Neural Repair
... We can register measurements like length, distance, displacements, time, angles. Using this data, we can further calculate force, velocity, acceleration, mechanical work, power, torque and so on (Liu, Stewart, Wiens, Mcnitt-Gray, Liu 2022). ...
November 2021
Computers in Biology and Medicine
... Many of the recent works regard the automatic segmentation as a pixel classification task and solve by U-shape convolutional neural networks (CNNs). Though some of the CNNs based methods can produce results with a very high overlap with the ground truth This article is part of the Topical Collection on Image & Signal Processing [3][4][5], compared to the performance of ophthalmologists, there still remains room for improvement which can help to advance the clinical application and adoption of automatic segmentation methods. Due to the separate probabilities thresholding of each output label, current pixel classification based methods may need extra post-processing such as hole filling, max component choosing, and ellipse fitting. ...
March 2019
... Agarwal et al. (2009) used a licorice gargle to reduce throat pain and coughing in postoperative patients; the licorice gargle significantly reduced the severity of throat pain, mainly due to its anti-inflammatory effects. Some clinical practices recommend a licorice mouthwash to relieve symptoms of mouth dryness following head or neck radiotherapy (Li, 2006). The objective of this study was to examine the effects of using a mouthwash with either pure water, or containing licorice to reduce xerostomia and improve saliva flow rates in hemodialysis patients. ...
March 2019
... 630 Papers covered histopathology whole-slide image and genomic data, 631 crowd-sourced image annotation 632 and many presentations on machine learning. [633][634][635][636][637][638][639] 3D printing was also of interest. 640 ...
March 2018
... [619][620][621][622][623] 3D printing papers were presented, 624,625 as were clinical decision support applications to reduce radiation dose. 626 Mobile devices were described for 3D wound care 627 and DICOM was still a topic at the meeting, this time for image quantification secondary capture. 628 ...
March 2017
Proceedings of SPIE - The International Society for Optical Engineering
... Moreover, from a translational perspective, most strokes that cause permanent deficits in humans are in the range of small to medium-sized infarcts. 37 Reducing infarct sizes while maintaining strong correlations of lesion volume and lesion location with symptom severity will aid the quality of translational research. Traditional pellet count may fall short in this endeavor, as for example this parameter could not distinguish between cortical and striatal lesions of comparable size in rats. ...
June 2017
Neurorehabilitation and Neural Repair
... This method can produce tissue compressions and generate a qualitative 2D image for evaluating the unknown tissue stiffness or strain, which produces chain compressions to the tissue using an impulsive, harmonic, and steady-state radiation force excitation [9][10][11][12][13]. As seen in Figure 1, this technique uses short-duration acoustic pulses with a fixed transmission frequency to locate tissue displacement, including the virtual touch tissue quantification mode [12] and the virtual touch tissue imaging (VTI) mode [14][15]. In the VTI mode, an algorithm can be used to transform the strain changes to indicate the 2D grayscale image of tissue stiffness in a region of interest (ROI) [16][17]. ...
February 2017
Proceedings of SPIE - The International Society for Optical Engineering
... Knowledgebased planning (KBP) provides a traditional paradigm for dose prediction that leverages planning information from historical patients to predict the dosimetry for a new patient [7,8]. Initially, some handcrafted features related to dosimetry are directly used to match historical patients with new patients, e.g., overlap volume histogram (OVH) [9], distance-to-target histogram (DTH) [10], and planning volume shapes [11]. With the development of machine learning technology, support vector regression, random forests, and gradient boosting have been used to find more effective features [12][13][14]. ...
April 2016
International Journal of Computer Assisted Radiology and Surgery
... 615 Deep learning and the combination of human and machine intelligence was explored in multiple papers. [616][617][618] ...
March 2016
Proceedings of SPIE - The International Society for Optical Engineering