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Alexandra Petukhova

Showing results (1-10 of 12) with videos related to

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Digestive Disease Interventions|September 2, 2020
Supervised Machine Learning in Oncology: A Clinician's GuideNikitha Murali, Ahmet Kucukkaya, Alexandra Petukhova, et al.
Insights Into Imaging|March 7, 2022
Changes of radiological examination volumes over the course of the COVID-19 pandemic: a comprehensive analysis of the different waves of infectionFlorian Nima Fleckenstein, Tazio Maleitzke, Georg Böning, et al.
Translational Oncology|October 19, 2020
Prediction of post-radiotherapy locoregional progression in HPV-associated oropharyngeal squamous cell carcinoma using machine-learning analysis of baseline PET/CT radiomicsStefan P Haider, Kariem Sharaf, Tal Zeevi, et al.
Journal of Vascular and Interventional Radiology : JVIR|December 19, 2021
Quantitative Automated Segmentation of Lipiodol Deposits on Cone-Beam CT Imaging Acquired during Transarterial Chemoembolization for Liver Tumors: A Deep Learning ApproachRohil Malpani, Christopher W Petty, Junlin Yang, et al.
Clinical Imaging|February 16, 2021
Thermal ablation alone vs thermal ablation combined with transarterial chemoembolization for patients with small (<3 cm) hepatocellular carcinomaNathan X Chai, Julius Chapiro, Alexandra Petukhova, et al.
European Radiology|October 30, 2020
Reliable prediction of survival in advanced-stage hepatocellular carcinoma treated with sorafenib: comparing 1D and 3D quantitative tumor response criteria on MRILuzie A Doemel, Julius Chapiro, Fabian Laage Gaupp, et al.
PLOS Digital Health|February 22, 2023
Cancer tracking system improves timeliness of liver cancer care at a Veterans Hospital: A comparison of cohorts before and after implementation of an automated care coordination toolYapei Zhang, Catherine Mezzacappa, Lin Shen, et al.
Journal of Vascular and Interventional Radiology : JVIR|November 24, 2022
MR Imaging-Based In Vivo Macrophage Imaging to Monitor Immune Response after Radiofrequency Ablation of the LiverJessica G Santana, Alexandra Petukhova-Greenstein, Moritz Gross, et al.
Scientific Reports|May 10, 2023
Predicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learningAhmet Said Kucukkaya, Tal Zeevi, Nathan Xianming Chai, et al.
AJR. American Journal of Roentgenology|August 17, 2022
Machine Learning Models for Prediction of Posttreatment Recurrence in Early-Stage Hepatocellular Carcinoma Using Pretreatment Clinical and MRI Features: A Proof-of-Concept StudySimon Iseke, Tal Zeevi, Ahmet S Kucukkaya, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Digestive Disease Interventions|September 2, 2020
Supervised Machine Learning in Oncology: A Clinician's GuideNikitha Murali, Ahmet Kucukkaya, Alexandra Petukhova, et al.
Insights Into Imaging|March 7, 2022
Changes of radiological examination volumes over the course of the COVID-19 pandemic: a comprehensive analysis of the different waves of infectionFlorian Nima Fleckenstein, Tazio Maleitzke, Georg Böning, et al.
Translational Oncology|October 19, 2020
Prediction of post-radiotherapy locoregional progression in HPV-associated oropharyngeal squamous cell carcinoma using machine-learning analysis of baseline PET/CT radiomicsStefan P Haider, Kariem Sharaf, Tal Zeevi, et al.
Journal of Vascular and Interventional Radiology : JVIR|December 19, 2021
Quantitative Automated Segmentation of Lipiodol Deposits on Cone-Beam CT Imaging Acquired during Transarterial Chemoembolization for Liver Tumors: A Deep Learning ApproachRohil Malpani, Christopher W Petty, Junlin Yang, et al.
Clinical Imaging|February 16, 2021
Thermal ablation alone vs thermal ablation combined with transarterial chemoembolization for patients with small (<3 cm) hepatocellular carcinomaNathan X Chai, Julius Chapiro, Alexandra Petukhova, et al.
European Radiology|October 30, 2020
Reliable prediction of survival in advanced-stage hepatocellular carcinoma treated with sorafenib: comparing 1D and 3D quantitative tumor response criteria on MRILuzie A Doemel, Julius Chapiro, Fabian Laage Gaupp, et al.
PLOS Digital Health|February 22, 2023
Cancer tracking system improves timeliness of liver cancer care at a Veterans Hospital: A comparison of cohorts before and after implementation of an automated care coordination toolYapei Zhang, Catherine Mezzacappa, Lin Shen, et al.
Journal of Vascular and Interventional Radiology : JVIR|November 24, 2022
MR Imaging-Based In Vivo Macrophage Imaging to Monitor Immune Response after Radiofrequency Ablation of the LiverJessica G Santana, Alexandra Petukhova-Greenstein, Moritz Gross, et al.
Scientific Reports|May 10, 2023
Predicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learningAhmet Said Kucukkaya, Tal Zeevi, Nathan Xianming Chai, et al.
AJR. American Journal of Roentgenology|August 17, 2022
Machine Learning Models for Prediction of Posttreatment Recurrence in Early-Stage Hepatocellular Carcinoma Using Pretreatment Clinical and MRI Features: A Proof-of-Concept StudySimon Iseke, Tal Zeevi, Ahmet S Kucukkaya, et al.
Pageof 2