2022
DOI: 10.1016/j.acra.2021.08.025
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Multi-Center Follow-up Study to Develop a Classification System Which Differentiates Mucinous Cystic Neoplasm of the Liver and Benign Hepatic Cyst Using Machine Learning

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Cited by 12 publications
(6 citation statements)
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“…By machine learning, Hardie AD. et al have summarized three imaging features that distinguish between BCA and BHC: solid enhancing nodule, all septations arising from an external macro-lobulation and whether solitary or one of multiple cystic liver lesions [ 14 ].…”
Section: Discussionmentioning
confidence: 99%
“…By machine learning, Hardie AD. et al have summarized three imaging features that distinguish between BCA and BHC: solid enhancing nodule, all septations arising from an external macro-lobulation and whether solitary or one of multiple cystic liver lesions [ 14 ].…”
Section: Discussionmentioning
confidence: 99%
“…The total accuracy of the proposed 4 type classification system was 93.5%, making it useful in risk-stratifying lesions for the likelihood of MCN diagnosis. 34 …”
Section: Diagnosismentioning
confidence: 99%
“…33 A recent multicenter follow-up study used machine learning to develop a classification system to differentiate MCNs from benign hepatic cysts. 34 The three imaging features that accurately differentiated MCNs from benign hepatic cysts were 1.) the presence of a solid enhancing nodule (100% specific), 2) lack of septations arising from external macrolobulations, and 3.)…”
mentioning
confidence: 99%
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“…The main application fields of deep learning in ultrasound computer-aided diagnosis system include breast disease diagnosis [15], liver disease diagnosis [16], fetal ultrasound standard plane detection [17], thyroid nodule diagnosis [18], and carotid artery ultrasound image classification [19]. In recent years, machine learning algorithms, such as decision tree (DT), support vector machine (SVM), K-nearest neighbors (KNN), and neural networks (NN), have been more and more frequently applied in medical field [20][21][22][23].…”
Section: Introductionmentioning
confidence: 99%