Fujitsu (Japan)

Detection of Cardiac Structural Abnormalities in Fetal Ultrasound Videos Using Deep Learning

Masaaki Komatsu, Akira Sakai, Reina Komatsu et al.

2021 · 133 Zit.

Classification of glomerular pathological findings using deep learning and nephrologist–AI collective intelligence approach

Eiichiro Uchino, Kanata Suzuki, Noriaki Sato et al.

2020 · 91 Zit.

Medical Professional Enhancement Using Explainable Artificial Intelligence in Fetal Cardiac Ultrasound Screening

Akira Sakai, Masaaki Komatsu, Reina Komatsu et al.

2022 · 64 Zit.

Lay User Involvement in Developing Human-centric Responsible AI Systems: When and How?

Beatrice Vincenzi, Simone Stumpf, Alex Taylor et al.

2024 · 10 Zit.

Taxonomy of Generative AI Applications for Risk Assessment

Hiroshi Tanaka, Masaru Ide, Jun Yajima et al.

2024 · 8 Zit.

EP24.14: Explainable AI to support examiners for abnormality detection in fetal cardiac ultrasound screening

Ryu Matsuoka, Akira Sakai, Masaaki Komatsu et al.

2023 · 1 Zit.

EARN Fairness: Explaining, Asking, Reviewing, and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholders

Lin Luo, Yuri Nakao, Mathieu Chollet et al.

2025 · 1 Zit.

PCN234 DEVELOPMENT AND VALIDATION STUDY OF ARTIFICIAL INTELLIGENCE SUPPORTING SYSTEMATIC LITERATURE REVIEW FOR CONDUCTING COST-EFFECTIVENESS ANALYSIS

Masao Ooishi, Mie Azuma, Hiroki Kitabayashi et al.

2019 · 0 Zit.

EP01.21: Performance evaluation study of an artificial intelligence‐based support system for fetal cardiac ultrasound screening

Reina Komatsu, Masaaki Komatsu, N. Harada et al.

2024 · 0 Zit.

EP02.49: The anatomical structure analysis in the cross‐vendor fetal cardiac ultrasound videos using deep learning

Masaaki Komatsu, N. Harada, H. Setoh et al.

2023 · 0 Zit.