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Accurate staging of liver fibrosis from magnetic resonance imaging (MRI) is crucial in clinical practice.
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Multiparametric CT for Noninvasive Staging of Hepatitis C Virus-Related Liver Fibrosis: Correlation with the Histopathologic Fibrosis Score
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Performance of a Generative Adversarial Network Using Ultrasound Images to Stage Liver Fibrosis and Predict Cirrhosis Based on a Deep-learning Radiomics Nomogram
Duan, Y.Y., Qin, J., Qiu, W.Q., Li, S.Y., Li, C., Liu, A.S., Chen, X., Zhang, C.X., 2022 · 2022
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Layer Ensembles: A Single-Pass Uncertainty Estimation in Deep Learning for Segmentation, in: Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 514–524
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Noninvasive Assessment of Liver Fibrosis and Inflammation in Chronic Hepatitis B: A Dual-Task Convolutional Neural Network (DTCNN) Model Based on Ultrasound Shear Wave Elastography
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Addressing deep learning model calibration using evidential neural networks and uncertainty-aware training, in: Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI), pp. 1–5
Dawood, T., Chan, E., Razavi, R., King, A.P., Puyol-Antón, E., 2023 · 2023
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A Reliable and Interpretable Framework of Multi-view Learning for Liver Fibrosis Staging, in: Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 178–188
Gao, Z., Liu, Y., Wu, F., Shi, N., Shi, Y., Zhuang, X., 2023 · 2023
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Adnet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement
Hansen, S., Gautam, S., Salahuddin, S.A., Kampffmeyer, M., Jenssen, R., 2023 · 2023
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Benchmarking common uncertainty estimation methods with histopathological images under domain shift and label noise
Mehrtens, H.A., Kurz, A., Bucher, T.C., Brinker, T.J., 2023 · 2023
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Evidential interactive learning for medical image captioning, in: Proceedings of the International Conference on Machine Learning (ICML), PMLR. pp. 42478–42491
Zheng, E., Yu, Q., 2023 · 2023
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New Bounds on the Accuracy of Majority Voting for Multiclass Classification
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