Ultrasound-based deep learning radiomics nomogram for differentiating mass mastitis from invasive breast cancer

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Bibliographische Detailangaben
Veröffentlicht in:	BMC Medical Imaging vol. 24 (2024), p. 1
1. Verfasser:	Wu, Linyong
Weitere Verfasser:	Li, Songhua, Wu, Chaojun, Wu, Shaofeng, Lin, Yan, Dayou Wei
Veröffentlicht:	Springer Nature B.V.
Schlagworte:	Datasets Wavelet transforms Supervised learning Phenotypes Unsupervised learning Data systems Image processing Machine learning Radiomics Decision trees Heterogeneity Physicians Clustering Lymphatic system Biopsy Ultrasound Information processing Computers Ultrasonic imaging Decision making Software Womens health Deep learning Models Visual discrimination learning Clinical medicine Nomograms Cancer therapies Mammography Information systems Work experience Medical imaging Breast cancer Learning algorithms Mastitis Cluster analysis Artificial intelligence Support vector machines Ultrasonic testing Neural networks Visual discrimination Vector quantization Invasiveness
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