AIMC Topic: Time-Lapse Imaging
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Embryo ranking agreement between embryologists and artificial intelligence algorithms.
F&S science
Oct 14, 2023
OBJECTIVE: To evaluate the degree of agreement of embryo ranking between embryologists and eight artificial intelligence (AI) algorithms.
A machine learning approach to predict cellular mechanical stresses in response to chemical perturbation.
Biophysical journal
Jul 25, 2023
Mechanical stresses generated at the cell-cell level and cell-substrate level have been suggested to be important in a host of physiological and pathological processes. However, the influence various chemical compounds have on the mechanical stresses...
Comparing performance between clinics of an embryo evaluation algorithm based on time-lapse images and machine learning.
Journal of assisted reproduction and genetics
Jul 10, 2023
PURPOSE: This article aims to assess how differences in maternal age distributions between IVF clinics affect the performance of an artificial intelligence model for embryo viability prediction and proposes a method to account for such differences.
Deep learning system for classification of ploidy status using time-lapse videos.
F&S science
Jun 30, 2023
OBJECTIVE: To develop a spatiotemporal model for de prediction of euploid and aneuploid embryos using time-lapse videos from 10-115 hours after insemination (hpi).
DeepSea is an efficient deep-learning model for single-cell segmentation and tracking in time-lapse microscopy.
Cell reports methods
Jun 12, 2023
Time-lapse microscopy is the only method that can directly capture the dynamics and heterogeneity of fundamental cellular processes at the single-cell level with high temporal resolution. Successful application of single-cell time-lapse microscopy re...
External validation of a model for selecting day 3 embryos for transfer based upon deep learning and time-lapse imaging.
Reproductive biomedicine online
Jun 3, 2023
RESEARCH QUESTION: Could objective embryo assessment using iDAScore Version 2.0 perform as well as conventional morphological assessment?
Deep learning for embryo evaluation using time-lapse: a systematic review of diagnostic test accuracy.
American journal of obstetrics and gynecology
Apr 26, 2023
OBJECTIVE: This study aimed to investigate the accuracy of convolutional neural network models in the assessment of embryos using time-lapse monitoring.
Development and validation of deep learning based embryo selection across multiple days of transfer.
Scientific reports
Mar 14, 2023
This work describes the development and validation of a fully automated deep learning model, iDAScore v2.0, for the evaluation of human embryos incubated for 2, 3, and 5 or more days. We trained and evaluated the model on an extensive and diverse dat...
Human induced pluripotent stem cell formation and morphology prediction during reprogramming with time-lapse bright-field microscopy images using deep learning methods.
Computer methods and programs in biomedicine
Nov 28, 2022
BACKGROUND AND OBJECTIVE: Human induced pluripotent stem cells (hiPSCs) represent an ideal source for patient specific cell-based regenerative medicine; however, efficiency of hiPSC formation from reprogramming cells is low. We use several deep-learn...
Association between a deep learning-based scoring system with morphokinetics and morphological alterations in human embryos.
Reproductive biomedicine online
Aug 13, 2022
RESEARCH QUESTION: What is the association between the deep learning-based scoring system, iDAScore, and biological events during the pre-implantation period?
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