Aniek F. Markus

The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies

2020 · 704 Zit. · Journal of Biomedical Informatics

Use of unstructured text in prognostic clinical prediction models: a systematic review

2022 · 73 Zit. · Journal of the American Medical Informatics Association

Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients

2022 · 35 Zit. · IEEE Transactions on Technology and Society

The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategies

2020 · 14 Zit. · Zenodo (CERN European Organization for Nuclear Research)

Use of unstructured text in prognostic clinical prediction models: a systematic review

2022 · 3 Zit.

Semantic Meaningfulness: Evaluating Counterfactual Approaches for Real-World Plausibility and Feasibility

2023 · 1 Zit. · Communications in computer and information science