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Norwegian University of Science and Technology

131.553 Arbeiten7.130.747 Zitationen
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Meistzitierte Publikationen im Bereich Gesundheit & MedTech

The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions

Keng‐Boon Ooi, Garry Wei‐Han Tan, Mostafa Al‐Emran et al.

2023 · 596 Zit.

The enlightening role of explainable artificial intelligence in medical & healthcare domains: A systematic literature review

Subhan Ali, Filza Akhlaq, Ali Shariq Imran et al.

2023 · 257 Zit.

Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation (PRIME): A Checklist

Partho P. Sengupta, Sirish Shrestha, Béatrice Berthon et al.

2020 · 205 Zit.

Explainable Artificial Intelligence (XAI) from a user perspective: A synthesis of prior literature and problematizing avenues for future research

AKM Bahalul Haque, A.K.M. Najmul Islam, Patrick Mikalef

2022 · 199 Zit.

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

Julia Amann, Dennis Vetter, Stig Nikolaj Fasmer Blomberg et al.

2022 · 191 Zit.

Responsible AI for Digital Health: a Synthesis and a Research Agenda

Cristina Trocin, Patrick Mikalef, Zacharoula Papamitsiou et al.

2021 · 175 Zit.

Assessing the Usability of ChatGPT for Formal English Language Learning

Sarang Shaikh, Sule Yildirim Yayilgan, Blanka Klímová et al.

2023 · 148 Zit.

How precision medicine and screening with big data could increase overdiagnosis

Henrik Vogt, Sara Green, Claus Thorn Ekstrøm et al.

2019 · 95 Zit.

A Comprehensive Survey of Digital Twins in Healthcare in the Era of Metaverse

Muhammad Turab, Sonain Jamil

2023 · 79 Zit.

Comparative analysis of explainable machine learning prediction models for hospital mortality

Eline Stenwig, Giampiero Salvi, Pierluigi Salvo Rossi et al.

2022 · 76 Zit.

Data Safe Havens in health research and healthcare

Paul R. Burton, Madeleine J. Murtagh, Andy Boyd et al.

2015 · 75 Zit.

The Enlightening Role of Explainable Artificial Intelligence in Chronic Wound Classification

Salih Sarp, Murat Kuzlu, Emmanuel Wilson et al.

2021 · 65 Zit.

REFORMS: Consensus-based Recommendations for Machine-learning-based Science

Sayash Kapoor, Emily M. Cantrell, Kenny Peng et al.

2024 · 64 Zit.

Possible strategies for use of artificial intelligence in screen-reading of mammograms, based on retrospective data from 122,969 screening examinations

Marthe Larsen, Camilla F. Aglen, Solveig Roth Hoff et al.

2022 · 63 Zit.

Enhancing wrist abnormality detection with YOLO: Analysis of state-of-the-art single-stage detection models

Ammar Ahmed, Ali Shariq Imran, Abdul Manaf et al.

2024 · 53 Zit.