AI Medical Compendium Topic

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Time-Lapse Imaging

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External validation of a model for selecting day 3 embryos for transfer based upon deep learning and time-lapse imaging.

Reproductive biomedicine online
RESEARCH QUESTION: Could objective embryo assessment using iDAScore Version 2.0 perform as well as conventional morphological assessment?

DeepSea is an efficient deep-learning model for single-cell segmentation and tracking in time-lapse microscopy.

Cell reports methods
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...

A machine learning approach to predict cellular mechanical stresses in response to chemical perturbation.

Biophysical journal
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...

Artificial intelligence in time-lapse system: advances, applications, and future perspectives in reproductive medicine.

Journal of assisted reproduction and genetics
With the rising demand for in vitro fertilization (IVF) cycles, there is a growing need for innovative techniques to optimize procedure outcomes. One such technique is time-lapse system (TLS) for embryo incubation, which minimizes environmental chang...

Embryo ranking agreement between embryologists and artificial intelligence algorithms.

F&S science
OBJECTIVE: To evaluate the degree of agreement of embryo ranking between embryologists and eight artificial intelligence (AI) algorithms.

Automated detection of apoptotic bodies and cells in label-free time-lapse high-throughput video microscopy using deep convolutional neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Reliable label-free methods are needed for detecting and profiling apoptotic events in time-lapse cell-cell interaction assays. Prior studies relied on fluorescent markers of apoptosis, e.g. Annexin-V, that provide an inconsistent and lat...

Deep Learning-Based Cell Tracking in Deforming Organs and Moving Animals.

Methods in molecular biology (Clifton, N.J.)
Cell tracking is an essential step in extracting cellular signals from moving cells, which is vital for understanding the mechanisms underlying various biological functions and processes, particularly in organs such as the brain and heart. However, c...

A novel machine-learning framework based on early embryo morphokinetics identifies a feature signature associated with blastocyst development.

Journal of ovarian research
BACKGROUND: Artificial Intelligence entails the application of computer algorithms to the huge and heterogeneous amount of morphodynamic data produced by Time-Lapse Technology. In this context, Machine Learning (ML) methods were developed in order to...

Machine learning in time-lapse imaging to differentiate embryos from young vs old mice†.

Biology of reproduction
Time-lapse microscopy for embryos is a non-invasive technology used to characterize early embryo development. This study employs time-lapse microscopy and machine learning to elucidate changes in embryonic growth kinetics with maternal aging. We anal...

Generative artificial intelligence to produce high-fidelity blastocyst-stage embryo images.

Human reproduction (Oxford, England)
STUDY QUESTION: Can generative artificial intelligence (AI) models produce high-fidelity images of human blastocysts?