Umeå University
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence
Zeynep Akata, Dan Balliet, Maarten de Rijke et al.
2020 · 362 Zit.
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir, Alejandro F. Frangi, Antonio R. Porras et al.
2025 · 300 Zit.
Explainable Agents and Robots: Results from a Systematic Literature Review
Sule Anjomshoae, Amro Najjar, Davide Calvaresi et al.
2019 · 215 Zit.
How to teach responsible AI in Higher Education: challenges and opportunities
Andrea Aler Tubella, Marçal Mora‐Cantallops, Juan Carlos Nieves
2023 · 100 Zit.
AI, Opacity, and Personal Autonomy
Bram Vaassen
2022 · 73 Zit.
Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion Classifier
Roberto V. Zicari, Sheraz Ahmed, Julia Amann et al.
2021 · 65 Zit.
A stacking classifiers model for detecting heart irregularities and predicting Cardiovascular Disease
Subasish Mohapatra, Sushree Maneesha, Subhadarshini Mohanty et al.
2022 · 52 Zit.
On Assessing Trustworthy AI in Healthcare. Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls
Roberto V. Zicari, James Brusseau, Stig Nikolaj Fasmer Blomberg et al.
2021 · 51 Zit.
Patients' perspectives related to ethical issues and risks in precision medicine: a systematic review
Lawko Ahmed, Anastasia Constantinidou, Andreas Chatzittofis
2023 · 50 Zit.
Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients
Felix Busch, Lena Hoffmann, Lina Xu et al.
2025 · 46 Zit.
Considerations for artificial intelligence clinical impact in oncologic imaging: an AI4HI position paper
Luis Martí‐Bonmatí, Dow‐Mu Koh, Katrine Riklund et al.
2022 · 32 Zit.
Responsible Artificial Intelligence --- From Principles to Practice
Virginia Dignum
2022 · 32 Zit.
Guiding principles for the use of knowledge bases and real-world data in clinical decision support systems: report by an international expert workshop at Karolinska Institutet
Mikael Hoffmann, Robert Vander Stichele, David W. Bates et al.
2020 · 25 Zit.
Helpful, harmless, honest? Sociotechnical limits of AI alignment and safety through Reinforcement Learning from Human Feedback
Adam Dahlgren Lindström, Leila Methnani, Lea Krause et al.
2025 · 24 Zit.
Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure
Luis Martí‐Bonmatí, Ignácio Blanquer, Manolis Tsiknakis et al.
2025 · 21 Zit.