Ivan S. Klyuzhin

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features

2022 · 20 Zit. · Computer Methods and Programs in Biomedicine

Testing the Ability of Convolutional Neural Networks to Learn Radiomic Features

2020 · 9 Zit. · medRxiv

Physician-in-the-Loop Active Learning in Radiology Artificial Intelligence Workflows: Opportunities, Challenges, and Future Directions

2025 · 3 Zit. · American Journal of Roentgenology

From code sharing to sharing of implementations: Advancing reproducible AI development for medical imaging through federated testing

2024 · 2 Zit. · Journal of medical imaging and radiation sciences

Clinician-interactive AI for RECIST measurements in CT imaging

2023 · 0 Zit.

RAIVEN: A novel framework for translation of AI tools to the radiology environment

2021 · 0 Zit.