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Julius Chapiro

Department of Radiology and Biomedical Imaging

Yale School of Medicine

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PUBLICATIONS

3D Quantitative tumour burden analysis in patients with hepatocellular carcinoma before TACE: comparing single-lesion vs. multi-lesion imaging biomarkers as predictors of patient survival.

European radiology Sep, 2016 | Pubmed ID: 26762942

Sorafenib in combination with transarterial chemoembolization for the treatment of hepatocellular carcinoma.

Clinical advances in hematology & oncology : H&O Aug, 2016 | Pubmed ID: 27487101

Intra-arterial therapies for liver cancer: assessing tumor response.

Expert review of anticancer therapy Feb, 2017 | Pubmed ID: 27983883

The impact of antiangiogenic therapy combined with Transarterial Chemoembolization on enhancement based quantitative tumor response assessment in patients with hepatocellular carcinoma.

Clinical imaging Nov - Dec, 2017 | Pubmed ID: 28668723

C-Arm Cone Beam CT for Intraprocedural Image Fusion and 3D Guidance in Portal Vein Embolization (PVE).

Cardiovascular and interventional radiology Mar, 2018 | Pubmed ID: 28875339

Clinical Experience with Real-Time 3-D Guidance Based on C-Arm-Acquired Cone-Beam CT (CBCT) in Transjugular Intrahepatic Portosystemic Stent Shunt (TIPSS) Placement.

Cardiovascular and interventional radiology Jul, 2018 | Pubmed ID: 29541837

Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning-An Artificial Intelligence Concept.

Journal of vascular and interventional radiology : JVIR 06, 2018 | Pubmed ID: 29548875

INSTITUTIONS

Yale School of Medicine

JOVE ARTICLES

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Aaron Abajian¹,

Nikitha Murali¹,

Lynn Jeanette Savic^1,2,

Fabian Max Laage-Gaupp¹,

Nariman Nezami¹,

James S. Duncan³,

Todd Schlachter¹,

MingDe Lin⁴,

Jean-François Geschwind⁵,

Julius Chapiro¹

¹Department of Radiology and Biomedical Imaging, Yale School of Medicine,

²Department of Diagnostic and Interventional Radiology, Universitätsmedizin Charité Berlin,

³Department of Biomedical Engineering, Yale School of Engineering and Applied Science,

⁴, Philips Research North America,

⁵, Prescience Labs

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Julius Chapiro

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Radiology and Biomedical Imaging

Yale School of Medicine

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Department of Radiology and Biomedical Imaging