Machine learning model development for quantitative analysis of CT heterogeneity in canine hepatic masses may predict histologic malignancy-Reference-Cited by-同舟云学术

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Machine learning model development for quantitative analysis of CT heterogeneity in canine hepatic masses may predict histologic malignancy

Published:2021-08-26 Issue:6 Volume:62 Page:711-719
ISSN:1058-8183
Container-title:Veterinary Radiology & Ultrasound
language:en
Short-container-title:Vet Radiology Ultrasound

Author:

Shaker Rami¹²^ORCID,Wilke Christopher³⁴^ORCID,Ober Christopher⁵,Lawrence Jessica⁴⁵^ORCID

Affiliation:

1. Institute for Health Informatics University of Minnesota Minneapolis Minnesota USA

2. Medical School University of Minnesota Minneapolis Minnesota USA

3. Department of Radiation Oncology Medical School University of Minnesota Minneapolis Minnesota USA

4. Masonic Cancer Center University of Minnesota Minneapolis Minnesota USA

5. Department of Veterinary Clinical Sciences, College of Veterinary Medicine University of Minnesota St Paul Minnesota USA

Publisher

Wiley

Subject

General Veterinary

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/vru.13012

Reference34 articles.

1. Ultrasonography, Computed Tomography and Magnetic Resonance Imaging of Hepatocellular Carcinoma: Toward Improved Treatment Decisions

2. TRIPLE-PHASE HELICAL COMPUTED TOMOGRAPHY IN DOGS WITH HEPATIC MASSES

3. Computed tomographic features for differentiating benign from malignant liver lesions in dogs

4. CT CHARACTERISTICS OF PRIMARY HEPATIC MASS LESIONS IN DOGS

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