Search Results for author:
Found 4 papers, 0 papers with code
Explainable Medical Imaging AI Needs Human-Centered Design: Guidelines and Evidence from a Systematic Review
To alleviate these shortcomings in forthcoming research while acknowledging the challenges of human-centered design in healthcare, we introduce the INTRPRT guideline, a systematic design directive for transparent ML systems in medical image analysis.
An Interpretable Algorithm for Uveal Melanoma Subtyping from Whole Slide Cytology Images
Algorithmic decision support is rapidly becoming a staple of personalized medicine, especially for high-stakes recommendations in which access to certain information can drastically alter the course of treatment, and thus, patient outcome; a prominent example is radiomics for cancer subtyping.
Deep Hiearchical Multi-Label Classification Applied to Chest X-Ray Abnormality Taxonomies
To this end, we present a deep HMLC approach for CXR CAD.
Anatomy-Aware Siamese Network: Exploiting Semantic Asymmetry for Accurate Pelvic Fracture Detection in X-ray Images
A new contrastive feature learning component in our Siamese network is designed to optimize the deep image features being more salient corresponding to the underlying semantic asymmetries (caused by pelvic fracture occurrences).
