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.- Annotation Uncertainty.
.- Uncertainty-Aware Bayesian Deep Learning with Noisy Training Labels for Epileptic Seizure Detection.
.- Active Learning for Scribble-based Diffusion MRI Segmentation.
.- FISHing in Uncertainty: Synthetic Contrastive Learning for Genetic Aberration Detection.
.- Diagnose with Uncertainty Awareness: Diagnostic Uncertainty Encoding Framework for Radiology Report Generation.
.- Clinical implementation of uncertainty modelling and risk management in clinical pipelines.
.- Making Deep Learning Models Clinically Useful - Improving Diagnostic Confidence in Inherited Retinal Disease with Conformal Prediction.
.- GUARDIAN: Guarding Against Uncertainty and Adversarial Risks in Robot-Assisted Surgeries.
.- Quality Control for Radiology Report Generation Models via Auxiliary Auditing Components.
.- Conformal Performance Range Prediction for Segmentation Output Quality Control.
.- Holistic Consistency for Subject-level Segmentation Quality Assessment in Medical Image Segmentation.
.- Out of distribution and domain shift identification and management.
.- CROCODILE: Causality aids RObustness via COntrastive DIsentangled LEarning.
.- Image-conditioned Diffusion Models for Medical Anomaly Detection.
.- Information Bottleneck-based Feature Weighting for Enhanced Medical Image Out-of-Distribution Detection.
.- Beyond Heatmaps: A Comparative Analysis of Metrics for Anomaly Localization in Medical Images.
.- Typicality excels Likelihood for Unsupervised Out-of-Distribution Detection in Medical Imaging.
.- Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection.
.- Uncertainty-Aware Vision Transformers for Medical Image Analysis.
.- Uncertainty modelling and estimation.
.- Efficient Precision control in Object Detection Models for Enhanced and Reliable Ovarian Follicle Counting.
.- GLANCE: Combating Label Noise using Global and Local Noise Correction for Multi-Label Chest X-ray Classification.
.- Conformal Prediction and Monte Carlo Inference for Addressing Uncertainty in Cervical Cancer Screening.
.- INFORMER- Interpretability Founded Monitoring of Medical Image Deep Learning.
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