HAL (France)
open access
Beyond Accuracy: Assessing the Trustworthiness of Deep Learning Models for Coronary CT Angiography
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- 3D Convolutional Neural Network for Predicting Clinical Outcome from Coronary Computed Tomography Angiography in Patients with Suspected Coronary Artery Disease.#258384
- Beyond visual inspection: the deep learning revolution in quantitative cerebrovascular imaging.#418355
- Multicentric Study for External Validation of a Deep Learning Model for Mammographic Breast Density Categorization#1306807
- Enhancing breast cancer detection accuracy through machine learning, deep learning and transfer learning techniques for clinical practice.#489469
- Deep Learning Optimizes the Diagnostic Performance of Coronary Computed Tomography Angiography in Heavily Calcified Coronary Plaques: A Chinese Multicenter Study.#1299577
Record · ID 1312286
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive