Binarized multi-gate mixture of Bayesian experts for cardiac syndrome X diagnosis: A clinician-in-the-loop scenario with a belief-uncertainty fusion paradigm.

Calibrating ensembles for scalable uncertainty quantification in deep learning-based medical image segmentation.

Navigating the development challenges in creating complex data systems.

Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation.

Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

Calibrating Ensembles for Scalable Uncertainty Quantification in Deep Learning-based Medical Segmentation.

Classification of datasets with imputed missing values: does imputation quality matter?

Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation.

A CUDA-powered method for the feature extraction and unsupervised analysis of medical images.

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans.

Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.

Incorporating Boundary Uncertainty into loss functions for biomedical image segmentation.

Advances in Artificial Intelligence to Reduce Polyp Miss Rates during Colonoscopy.

A Mixed Focal Loss Function for Handling Class Imbalanced Medical Image Segmentation.

3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning.

Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy.

MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction.

Recent advances of HCI in decision-making tasks for optimized clinical workflows and precision medicine.

A Survey on Nature-Inspired Medical Image Analysis: A Step Further in Biomedical Data Integration.

Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review.

Tissue-specific and interpretable sub-segmentation of whole tumour burden on CT images by unsupervised fuzzy clustering.

Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images.