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Characterisation of prostate cancer using texture analysis for diagnostic and prognostic monitoring - Singh - 2021 - NMR in Biomedicine - Wiley Online Library
Deep learning applications in radiology: a deep dive on classification
A breakage kernel for use in population balance modelling of twin screw granulation - ScienceDirect
Example of ECG modeling by Gaussian kernel functions: a) the original... | Download Scientific Diagram
Tomography | Free Full-Text | AI Lung Segmentation and Perfusion Analysis of Dual-Energy CT Can Help to Distinguish COVID-19 Infiltrates from Visually Similar Immunotherapy-Related Pneumonitis Findings and Can Optimize Radiological Workflows
PDF] Machine Learning Approaches to Automatic BI-RADS Classification of Mammography Reports | Semantic Scholar
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Characterisation of prostate cancer using texture analysis for diagnostic and prognostic monitoring - Singh - 2021 - NMR in Biomedicine - Wiley Online Library
Bubble population balance modelling for stationary and rotating columns under zero-gravity environment: Numerical study - Yousuf Alhendal, Ali Turan, Abdulrahim Kalendar, Hosny Abou-Ziyan, 2019
Automated annotation and classification of BI-RADS assessment from radiology reports - ScienceDirect
Frontiers | Quantitative parameters of enhanced dual-energy computed tomography for differentiating lung cancers from benign lesions in solid pulmonary nodules
Machine intelligence in non-invasive endocrine cancer diagnostics | Nature Reviews Endocrinology
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Frontiers | Diagnosis of Breast Cancer Using Radiomics Models Built Based on Dynamic Contrast Enhanced MRI Combined With Mammography
CAD-RADS: Pushing the Limits | RadioGraphics
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Cancers | Free Full-Text | A Novel Nodule Edge Sharpness Radiomic Biomarker Improves Performance of Lung-RADS for Distinguishing Adenocarcinomas from Granulomas on Non-Contrast CT Scans
PDF] Deep learning LI-RADS grading system based on contrast enhanced multiphase MRI for differentiation between LR-3 and LR-4/LR-5 liver tumors | Semantic Scholar
Sensors | Free Full-Text | A High-Performance Deep Neural Network Model for BI-RADS Classification of Screening Mammography
Frontiers | CT-Based Pelvic T1-Weighted MR Image Synthesis Using UNet, UNet++ and Cycle-Consistent Generative Adversarial Network (Cycle-GAN)
Example of ECG modeling by Gaussian kernel functions: a) the original... | Download Scientific Diagram
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