29 results on '"Tiulpin A"'
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2. Active Sensing of Knee Osteoarthritis Progression with Reinforcement Learning.
3. Image-level Regression for Uncertainty-aware Retinal Image Segmentation.
4. SiNGR: Brain Tumor Segmentation via Signed Normalized Geodesic Transform Regression.
5. Understanding metric-related pitfalls in image analysis validation.
6. End-To-End Prediction of Knee Osteoarthritis Progression With Multi-Modal Transformers.
7. Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection.
8. Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors.
9. A Stronger Baseline For Automatic Pfirrmann Grading Of Lumbar Spine MRI Using Deep Learning.
10. Predicting Knee Osteoarthritis Progression from Structural MRI using Deep Learning.
11. AdaTriplet: Adaptive Gradient Triplet Loss with Automatic Margin Learning for Forensic Medical Image Matching.
12. On confidence intervals for precision matrices and the eigendecomposition of covariance matrices.
13. Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multimodal Data.
14. DeepProg: A Transformer-based Framework for Predicting Disease Prognosis.
15. Targeted Active Learning for Bayesian Decision-Making.
16. Greedy Bayesian Posterior Approximation with Deep Ensembles.
17. Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading from Plain Radiographs.
18. Deep Learning for Wrist Fracture Detection: Are We There Yet?
19. Breast Tumor Cellularity Assessment using Deep Neural Networks.
20. Deep-Learning for Tidemark Segmentation in Human Osteochondral Tissues Imaged with Micro-computed Tomography.
21. Bayesian Feature Pyramid Networks for Automatic Multi-Label Segmentation of Chest X-rays and Assessment of Cardio-Thoratic Ratio.
22. Improving Robustness of Deep Learning Based Knee MRI Segmentation: Mixup and Adversarial Domain Adaptation.
23. Adaptive Segmentation of Knee Radiographs for Selecting the Optimal ROI in Texture Analysis.
24. KNEEL: Knee Anatomical Landmark Localization Using Hourglass Networks.
25. Automatic Grading of Individual Knee Osteoarthritis Features in Plain Radiographs using Deep Convolutional Neural Networks.
26. Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data.
27. DGC-Net: Dense Geometric Correspondence Network.
28. Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep Learning-Based Approach.
29. A novel method for automatic localization of joint area on knee plain radiographs.
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