Automated Machine Learning in the Sonographic Diagnosis of Non-alcoholic Fatty Liver Disease

Automated Machine Learning in the Sonographic Diagnosis of Non-alcoholic Fatty Liver Disease

Objective: This study evaluated the performance of automated machine-learning to diagnose non-alcoholic fatty liver disease (NAFLD) by ultrasound and compared these findings to radiologist performance.Methods: 96 patients with histologic (33) or proton density fat fraction MRI (63) diagnosis of NAFL...

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Bibliographic Details
Main Author: Sriharsha Gummadi, MD, Nirmal Patel, Haresh Naringrekar, MD, Laurence Needleman, MD, Andrej Lyshchik, MD PhD, Patrick O’Kane, MD, Jesse Civan, MD, John R Eisenbrey, PhD
Format: Article
Language:English
Published: Editorial Office of Advanced Ultrasound in Diagnosis and Therapy 2020-09-01
Series:Advanced Ultrasound in Diagnosis and Therapy
Subjects:
|non-alcoholic fatty liver disease|machine learning|ultrasound
Online Access:http://www.journaladvancedultrasound.com:81/fileup/2576-2516/PDF/1597831392870-1963498553.pdf

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http://www.journaladvancedultrasound.com:81/fileup/2576-2516/PDF/1597831392870-1963498553.pdf

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