Article

Construction of a Standardized Time-Lapse Imaging Database and a Gradient Boosting Ensemble Framework for Integrating Zygote Morphokinetic Parameters with Conventional Embryo Assessment

2026-08-24

Abstract excerpt

In vitro fertilization (IVF) laboratories equipped with timelapse incubators generate vast quantities of sequential embryo images, yet the absence of standardized, annotated databases impedes the development of reproducible computational tools for embryo assessment. Here we describe the construction of a standardized time-lapse imaging database comprising 631 normally fertilized zygotes from 218 treatment cycles,...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 4ff82c66-10cb-5eb8-8965-5d3d546557ee
DOI: 10.64898/2026.08.20.26359523

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Construction of a Standardized Time-Lapse Imaging Database and a Gradient Boosting Ensemble Framework for Integrating Zygote Morphokinetic Parameters with Conventional Embryo AssessmentDOI 10.64898/2026.08.20.26359523Read

Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequencesSemantic proximity Read

Development and validation of deep learning based embryo selection across multiple days of transferSemantic proximity Read

Delineating the heterogeneity of embryo preimplantation development using automated and accurate morphokinetic annotationSemantic proximity Read

Internal and External Validation of an Ensemble Learning Model Integrating Zygote Morphokinetics with Conventional Embryo Assessment for Blastocyst PredictionSemantic proximity Read

Automated Evaluation of Human Embryo Blastulation and Implantation Potential using Deep‐LearningSemantic proximity Read

A clinical consensus-compliant deep learning approach to quantitatively evaluate human in vitro fertilization early embryonic development with optical microscope imagesSemantic proximity Read

Towards Automation in IVF: Pre-Clinical Validation of a Deep Learning-Based Embryo Grading System during PGT-A CyclesSemantic proximity Read

Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilizationSemantic proximity Read

An artificial intelligence tool predicts blastocyst development from static images of fresh mature oocytesSemantic proximity Read

Automated Embryo Selection Using Deep Learning: A Comparative Study of 3D-CNN, Hybrid, and Transfer Learning ModelsSemantic proximity Read

Deep learning methods to forecasting human embryo development in time-lapse videosSemantic proximity Read

Development of automated annotation software for human embryo morphokineticsSemantic proximity Read