Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Fabien Scalzo

Showing results (21-30 of 89) with videos related to

Pageof 9
Sort By:
IEEE Transactions on Bio-Medical Engineering|July 11, 2018
Prediction of Hemorrhagic Transformation Severity in Acute Stroke From Source Perfusion MRIYannan Yu, Danfeng Guo, Min Lou, et al.
Artificial Intelligence in Medicine|October 5, 2011
Bayesian tracking of intracranial pressure signal morphologyFabien Scalzo, Shadnaz Asgari, Sunghan Kim, et al.
Technology in Cancer Research & Treatment|November 10, 2018
Performance Comparison of Knowledge-Based Dose Prediction Techniques Based on Limited Patient DataAngelia Landers, Ryan Neph, Fabien Scalzo, et al.
IEEE Transactions on Bio-Medical Engineering|March 11, 2009
Morphological clustering and analysis of continuous intracranial pressureXiao Hu, Peng Xu, Fabien Scalzo, et al.
Medical & Biological Engineering & Computing|July 7, 2009
Regression analysis for peak designation in pulsatile pressure signalsFabien Scalzo, Peng Xu, Shadnaz Asgari, et al.
Medical Engineering & Physics|March 10, 2012
Intracranial hypertension prediction using extremely randomized decision treesFabien Scalzo, Robert Hamilton, Shadnaz Asgari, et al.
Biomedical Engineering Online|October 21, 2010
Robust peak recognition in intracranial pressure signalsFabien Scalzo, Shadnaz Asgari, Sunghan Kim, et al.
Proceedings. IEEE International Symposium on Biomedical Imaging|January 27, 2022
INTEGRATIVE RADIOMICS MODELS TO PREDICT BIOPSY RESULTS FOR NEGATIVE PROSTATE MRIHaoxin Zheng, Qi Miao, Steven S Raman, et al.
Frontiers in Neurology|September 21, 2018
A Machine Learning Approach to Perfusion Imaging With Dynamic Susceptibility Contrast MRRichard McKinley, Fan Hung, Roland Wiest, et al.
Nature Reviews. Nephrology|March 4, 2026
Bridging structure and function: artificial intelligence-based modelling of kidney proteinsSean Wu, Weiguang Wang, Z Hong Zhou, et al.
Pageof 9

Showing results (21-30 of 89) with videos related to

Sort By:
Pageof 9
IEEE Transactions on Bio-Medical Engineering|July 11, 2018
Prediction of Hemorrhagic Transformation Severity in Acute Stroke From Source Perfusion MRIYannan Yu, Danfeng Guo, Min Lou, et al.
Artificial Intelligence in Medicine|October 5, 2011
Bayesian tracking of intracranial pressure signal morphologyFabien Scalzo, Shadnaz Asgari, Sunghan Kim, et al.
Technology in Cancer Research & Treatment|November 10, 2018
Performance Comparison of Knowledge-Based Dose Prediction Techniques Based on Limited Patient DataAngelia Landers, Ryan Neph, Fabien Scalzo, et al.
IEEE Transactions on Bio-Medical Engineering|March 11, 2009
Morphological clustering and analysis of continuous intracranial pressureXiao Hu, Peng Xu, Fabien Scalzo, et al.
Medical & Biological Engineering & Computing|July 7, 2009
Regression analysis for peak designation in pulsatile pressure signalsFabien Scalzo, Peng Xu, Shadnaz Asgari, et al.
Medical Engineering & Physics|March 10, 2012
Intracranial hypertension prediction using extremely randomized decision treesFabien Scalzo, Robert Hamilton, Shadnaz Asgari, et al.
Biomedical Engineering Online|October 21, 2010
Robust peak recognition in intracranial pressure signalsFabien Scalzo, Shadnaz Asgari, Sunghan Kim, et al.
Proceedings. IEEE International Symposium on Biomedical Imaging|January 27, 2022
INTEGRATIVE RADIOMICS MODELS TO PREDICT BIOPSY RESULTS FOR NEGATIVE PROSTATE MRIHaoxin Zheng, Qi Miao, Steven S Raman, et al.
Frontiers in Neurology|September 21, 2018
A Machine Learning Approach to Perfusion Imaging With Dynamic Susceptibility Contrast MRRichard McKinley, Fan Hung, Roland Wiest, et al.
Nature Reviews. Nephrology|March 4, 2026
Bridging structure and function: artificial intelligence-based modelling of kidney proteinsSean Wu, Weiguang Wang, Z Hong Zhou, et al.
Pageof 9