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Ida Arvidsson

Showing results (21-30 of 33) with videos related to

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Medical Physics|December 21, 2025
Dual energy CT and deep learning for an automated volumetric segmentation of the major intracranial tissues: Feasibility and initial findingsVeronica Fransson, Filip Winzell, Birgitta Ramgren, et al.
Advances in Experimental Medicine and Biology|August 27, 2015
Complement Interactions with Blood Cells, Endothelial Cells and Microvesicles in Thrombotic and Inflammatory ConditionsDiana Karpman, Anne-lie Ståhl, Ida Arvidsson, et al.
Scientific Reports|October 9, 2019
Shiga toxin signals via ATP and its effect is blocked by purinergic receptor antagonismKarl E Johansson, Anne-Lie Ståhl, Ida Arvidsson, et al.
Alzheimer'S Research & Therapy|March 20, 2024
Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with mild cognitive symptomsIda Arvidsson, Olof Strandberg, Sebastian Palmqvist, et al.
Research Square|November 21, 2023
Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with mild cognitive symptomsIda Arvidsson, Olof Strandberg, Sebastian Palmqvist, et al.
Plos Pathogens|February 27, 2015
A novel mechanism of bacterial toxin transfer within host blood cell-derived microvesiclesAnne-lie Ståhl, Ida Arvidsson, Karl E Johansson, et al.
Journal of Immunology (Baltimore, Md. : 1950)|February 1, 2015
Shiga toxin-induced complement-mediated hemolysis and release of complement-coated red blood cell-derived microvesicles in hemolytic uremic syndromeIda Arvidsson, Anne-Lie Ståhl, Minola Manea Hedström, et al.
NPJ Digital Medicine|July 10, 2025
Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancerDaqu Zhang, Looket Dihge, Pär-Ola Bendahl, et al.
Medrxiv : the Preprint Server for Health Sciences|June 10, 2024
A machine learning-based prediction of tau load and distribution in Alzheimer's disease using plasma, MRI and clinical variablesLinda Karlsson, Jacob Vogel, Ida Arvidsson, et al.
Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association|February 22, 2025
Machine learning prediction of tau-PET in Alzheimer's disease using plasma, MRI, and clinical dataLinda Karlsson, Jacob Vogel, Ida Arvidsson, et al.
Pageof 4

Showing results (21-30 of 33) with videos related to

Sort By:
Pageof 4
Medical Physics|December 21, 2025
Dual energy CT and deep learning for an automated volumetric segmentation of the major intracranial tissues: Feasibility and initial findingsVeronica Fransson, Filip Winzell, Birgitta Ramgren, et al.
Advances in Experimental Medicine and Biology|August 27, 2015
Complement Interactions with Blood Cells, Endothelial Cells and Microvesicles in Thrombotic and Inflammatory ConditionsDiana Karpman, Anne-lie Ståhl, Ida Arvidsson, et al.
Scientific Reports|October 9, 2019
Shiga toxin signals via ATP and its effect is blocked by purinergic receptor antagonismKarl E Johansson, Anne-Lie Ståhl, Ida Arvidsson, et al.
Alzheimer'S Research & Therapy|March 20, 2024
Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with mild cognitive symptomsIda Arvidsson, Olof Strandberg, Sebastian Palmqvist, et al.
Research Square|November 21, 2023
Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with mild cognitive symptomsIda Arvidsson, Olof Strandberg, Sebastian Palmqvist, et al.
Plos Pathogens|February 27, 2015
A novel mechanism of bacterial toxin transfer within host blood cell-derived microvesiclesAnne-lie Ståhl, Ida Arvidsson, Karl E Johansson, et al.
Journal of Immunology (Baltimore, Md. : 1950)|February 1, 2015
Shiga toxin-induced complement-mediated hemolysis and release of complement-coated red blood cell-derived microvesicles in hemolytic uremic syndromeIda Arvidsson, Anne-Lie Ståhl, Minola Manea Hedström, et al.
NPJ Digital Medicine|July 10, 2025
Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancerDaqu Zhang, Looket Dihge, Pär-Ola Bendahl, et al.
Medrxiv : the Preprint Server for Health Sciences|June 10, 2024
A machine learning-based prediction of tau load and distribution in Alzheimer's disease using plasma, MRI and clinical variablesLinda Karlsson, Jacob Vogel, Ida Arvidsson, et al.
Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association|February 22, 2025
Machine learning prediction of tau-PET in Alzheimer's disease using plasma, MRI, and clinical dataLinda Karlsson, Jacob Vogel, Ida Arvidsson, et al.
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