Search Results for author:
Found 6 papers, 2 papers with code
MDF-Net for abnormality detection by fusing X-rays with clinical data
In this work, we propose a novel architecture consisting of two fusion methods that enable the model to simultaneously process patients' clinical data (structured data) and chest X-rays (image data).
Development of an Immersive Virtual Colonoscopy Viewer for Colon Growths Diagnosis
Desktop-based virtual colonoscopy has been proven to be an asset in the identification of colon anomalies.
Integrating Eye-Gaze Data into CXR DL Approaches: A Preliminary study
This paper proposes a novel multimodal DL architecture incorporating medical images and eye-tracking data for abnormality detection in chest x-rays.
Benchmarking Counterfactual Algorithms for XAI: From White Box to Black Box
This study investigates the impact of machine learning models on the generation of counterfactual explanations by conducting a benchmark evaluation over three different types of models: decision-tree (fully transparent, interpretable, white-box model), a random forest (a semi-interpretable, grey-box model), and a neural network (a fully opaque, black-box model).
Improving X-ray Diagnostics through Eye-Tracking and XR
There is a growing need to assist radiologists in performing X-ray readings and diagnoses fast, comfortably, and effectively.
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications
This paper presents an in-depth systematic review of the diverse existing body of literature on counterfactuals and causability for explainable artificial intelligence.
