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Alex Zwanenburg

Showing results (31-40 of 47) with videos related to

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Plos One|April 17, 2018
ST waveform analysis for monitoring hypoxic distress in fetal sheep after prolonged umbilical cord occlusionPeter Andriessen, Alex Zwanenburg, Judith O E H van Laar, et al.
Plos One|August 31, 2013
Mesenchymal stem cells induce T-cell tolerance and protect the preterm brain after global hypoxia-ischemiaReint K Jellema, Tim G A M Wolfs, Valéria Lima Passos, et al.
Nature Reviews. Clinical Oncology|September 3, 2025
Radiomics Quality Score 2.0: towards radiomics readiness levels and clinical translation for personalized medicinePhilippe Lambin, Henry C Woodruff, Shruti Atul Mali, et al.
Nature Cancer|February 5, 2022
An artificial intelligence framework integrating longitudinal electronic health records with real-world data enables continuous pan-cancer prognosticationOlivier Morin, Martin Vallières, Steve Braunstein, et al.
International Journal of Surgery (London, England)|March 27, 2025
AutoFRS: an externally validated, annotation-free approach to computational preoperative complication risk stratification in pancreatic surgery - an experimental studyFiona R Kolbinger, Nithya Bhasker, Felix Schön, et al.
Experimental Neurology|October 15, 2013
Systemic G-CSF attenuates cerebral inflammation and hypomyelination but does not reduce seizure burden in preterm sheep exposed to global hypoxia-ischemiaReint K Jellema, Valéria Lima Passos, Daan R M G Ophelders, et al.
Cancers|October 14, 2023
Multitask Learning with Convolutional Neural Networks and Vision Transformers Can Improve Outcome Prediction for Head and Neck Cancer PatientsSebastian Starke, Alex Zwanenburg, Karoline Leger, et al.
Cancers|October 22, 2020
Comprehensive Analysis of Tumour Sub-Volumes for Radiomic Risk Modelling in Locally Advanced HNSCCStefan Leger, Alex Zwanenburg, Karoline Leger, et al.
Scientific Reports|October 18, 2017
A comparative study of machine learning methods for time-to-event survival data for radiomics risk modellingStefan Leger, Alex Zwanenburg, Karoline Pilz, et al.
Scientific Reports|October 6, 2022
Integrated radiogenomics analyses allow for subtype classification and improved outcome prognosis of patients with locally advanced HNSCCAsier Rabasco Meneghetti, Alex Zwanenburg, Annett Linge, et al.
Pageof 5

Showing results (31-40 of 47) with videos related to

Sort By:
Pageof 5
Plos One|April 17, 2018
ST waveform analysis for monitoring hypoxic distress in fetal sheep after prolonged umbilical cord occlusionPeter Andriessen, Alex Zwanenburg, Judith O E H van Laar, et al.
Plos One|August 31, 2013
Mesenchymal stem cells induce T-cell tolerance and protect the preterm brain after global hypoxia-ischemiaReint K Jellema, Tim G A M Wolfs, Valéria Lima Passos, et al.
Nature Reviews. Clinical Oncology|September 3, 2025
Radiomics Quality Score 2.0: towards radiomics readiness levels and clinical translation for personalized medicinePhilippe Lambin, Henry C Woodruff, Shruti Atul Mali, et al.
Nature Cancer|February 5, 2022
An artificial intelligence framework integrating longitudinal electronic health records with real-world data enables continuous pan-cancer prognosticationOlivier Morin, Martin Vallières, Steve Braunstein, et al.
International Journal of Surgery (London, England)|March 27, 2025
AutoFRS: an externally validated, annotation-free approach to computational preoperative complication risk stratification in pancreatic surgery - an experimental studyFiona R Kolbinger, Nithya Bhasker, Felix Schön, et al.
Experimental Neurology|October 15, 2013
Systemic G-CSF attenuates cerebral inflammation and hypomyelination but does not reduce seizure burden in preterm sheep exposed to global hypoxia-ischemiaReint K Jellema, Valéria Lima Passos, Daan R M G Ophelders, et al.
Cancers|October 14, 2023
Multitask Learning with Convolutional Neural Networks and Vision Transformers Can Improve Outcome Prediction for Head and Neck Cancer PatientsSebastian Starke, Alex Zwanenburg, Karoline Leger, et al.
Cancers|October 22, 2020
Comprehensive Analysis of Tumour Sub-Volumes for Radiomic Risk Modelling in Locally Advanced HNSCCStefan Leger, Alex Zwanenburg, Karoline Leger, et al.
Scientific Reports|October 18, 2017
A comparative study of machine learning methods for time-to-event survival data for radiomics risk modellingStefan Leger, Alex Zwanenburg, Karoline Pilz, et al.
Scientific Reports|October 6, 2022
Integrated radiogenomics analyses allow for subtype classification and improved outcome prognosis of patients with locally advanced HNSCCAsier Rabasco Meneghetti, Alex Zwanenburg, Annett Linge, et al.
Pageof 5