3 citations · 6 across the 9 of their papers we have counts for
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Methodological Explainability Evaluation of an Interpretable Deep Learning Model for Post-Hepatectomy Liver Failure Prediction Incorporating Counterfactual Explanations and Layerwise Relevance Propagation: A Prospective In Silico Trial
Xian Zhong, Zohaib Salahuddin, Yi Chen +15
Artificial intelligence (AI)-based decision support systems have demonstrated value in predicting post-hepatectomy liver failure (PHLF) in hepatocellular carcinoma (HCC). However,…
Counterfactuals and Uncertainty-Based Explainable Paradigm for the Automated Detection and Segmentation of Renal Cysts in Computed Tomography Images: A Multi-Center Study
Zohaib Salahuddin, Abdalla Ibrahim, Sheng Kuang +10
Routine computed tomography (CT) scans often detect a wide range of renal cysts, some of which may be malignant. Early and precise localization of these cysts can significantly aid…
A review of handcrafted and deep radiomics in neurological diseases: transitioning from oncology to clinical neuroimaging
Elizaveta Lavrova, Henry C. Woodruff, Hamza Khan +3
Medical imaging technologies have undergone extensive development, enabling non-invasive visualization of clinical information. The traditional review of medical images by clinicia…