5 papers
Knowledge-based anomaly detection for identifying network-induced shape artifacts
Rucha Deshpande, Tahsin Rahman, Miguel Lago +6
Synthetic data provides a promising approach to address data scarcity for training machine learning models; however, adoption without proper quality assessments may introduce artif…
HistoART: Histopathology Artifact Detection and Reporting Tool
Seyed Kahaki, Alexander R. Webber, Ghada Zamzmi +3
In modern cancer diagnostics, Whole Slide Imaging (WSI) is widely used to digitize tissue specimens for detailed, high-resolution examination; however, other diagnostic approaches,…
Evaluating Explainability: A Framework for Systematic Assessment and Reporting of Explainable AI Features
Miguel A. Lago, Ghada Zamzmi, Brandon Eich +1
Explainability features are intended to provide insight into the internal mechanisms of an AI device, but there is a lack of evaluation techniques for assessing the quality of prov…
Scorecards for Synthetic Medical Data Evaluation and Reporting
Ghada Zamzmi, Adarsh Subbaswamy, Elena Sizikova +3
Although interest in synthetic medical data (SMD) for training and testing AI methods is growing, the absence of a standardized framework to evaluate its quality and applicability…
Synthetic Data in Radiological Imaging: Current State and Future Outlook
Elena Sizikova, Andreu Badal, Jana G. Delfino +6
A key challenge for the development and deployment of artificial intelligence (AI) solutions in radiology is solving the associated data limitations. Obtaining sufficient and repre…