Vince I. Madai

Explainability for artificial intelligence in healthcare: a multidisciplinary perspective

2020 · 1.698 Zit. · BMC Medical Informatics and Decision Making

To explain or not to explain?—Artificial intelligence explainability in clinical decision support systems

2022 · 194 Zit. · PLOS Digital Health

Opening the black box of artificial intelligence for clinical decision support: A study predicting stroke outcome

2020 · 183 Zit. · PLoS ONE

You Can’t Have AI Both Ways: Balancing Health Data Privacy and Access Fairly

2022 · 107 Zit. · Frontiers in Genetics

From Bit to Bedside: A Practical Framework for Artificial Intelligence Product Development in Healthcare

2020 · 102 Zit. · Advanced Intelligent Systems

A trustworthy AI reality-check: the lack of transparency of artificial intelligence products in healthcare

2024 · 94 Zit. · Frontiers in Digital Health

Expectations and attitudes towards medical artificial intelligence: A qualitative study in the field of stroke

2023 · 89 Zit. · PLoS ONE

Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion Classifier

2021 · 65 Zit. · Frontiers in Human Dynamics

Artificial Intelligence for Clinical Decision Support in Acute Ischemic Stroke: A Systematic Review

2023 · 56 Zit. · Stroke

On Assessing Trustworthy AI in Healthcare. Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls

2021 · 51 Zit. · Frontiers in Human Dynamics

The Impact of Multi-Institution Datasets on the Generalizability of Machine Learning Prediction Models in the ICU

2024 · 51 Zit. · Critical Care Medicine

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

Lessons Learned from Assessing Trustworthy AI in Practice

2023 · 24 Zit. · Digital Society

The unmet promise of trustworthy AI in healthcare: why we fail at clinical translation

2024 · 19 Zit. · Frontiers in Digital Health

Opening the Black Box of Artificial Intelligence for Clinical Decision Support: A Study Predicting Stroke Outcome

2019 · 14 Zit. · medRxiv