ClinicalTrials.gov
public full text
Public Domain
Application of Deep Learning to Jointly Assess Embryo Development to Improve Pregnancy Outcome of Embryo Transfer
Aim of this research is to apply the deep learning automation based on Time-lapse imaging to jointly assess embryo development，so that it can ensure the consistency of embryo evaluation and improve the accuracy of evaluation.
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
- A deep learning based NeuroFusionNet approach for automated brain tumor diagnosis from MRI.#150302
- Clinical Grading of Artificial Intelligence-Based 3D Fetal Brain Segmentations: A Cross-Vendor Evaluation of Deep Learning in Fetal Neuroimaging.#4339
- An interpretable ultrasound-based deep learning system for early breast cancer in a Chinese population.#265450
- Impact of simulated MRI artifacts on deep learning-based brain age prediction#133112
- Impact of simulated MRI artifacts on deep learning-based brain age prediction#131035
Record · ID 1294285
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