logo
ResearchBunny Logo
Uncovering developmental time and tempo using deep learning

Biology

Uncovering developmental time and tempo using deep learning

N. Toulany, H. Morales-navarrete, et al.

Discover an innovative automated deep learning approach that uses Twin Networks for analyzing embryonic development, developed by Nikan Toulany and colleagues. This research not only facilitates accurate embryo staging but also quantifies temperature-dependent developmental tempo and uncovers developmental abnormalities, paving the way for creating staging atlases across various species. Dive into the future of embryogenesis analysis!

00:00
00:00
Playback language: English
Citation Metrics
Citations
0
Influential Citations
0
Reference Count
0

Note: The citation metrics presented here have been sourced from Semantic Scholar and OpenAlex.

Related Publications

Explore these studies to deepen your understanding of the subject.

Recent Advancements and Perspectives in the Diagnosis of Skin Diseases Using Machine Learning and Deep Learning: A Review
Medicine and Health

Recent Advancements and Perspectives in the Diagnosis of Skin Diseases Using Machine Learning and Deep Learning: A Review

J. Zhang, F. Zhong, et al.

Design and Analysis of a Deep Learning Ensemble Framework Model for the Detection of COVID-19 and Pneumonia Using Large-Scale CT Scan and X-ray Image Datasets
Medicine and Health

Design and Analysis of a Deep Learning Ensemble Framework Model for the Detection of COVID-19 and Pneumonia Using Large-Scale CT Scan and X-ray Image Datasets

X. Xue, S. Chinnaperumal, et al.

Nondestructive monitoring of annealing and chemical-mechanical planarization behavior using ellipsometry and deep learning
Engineering and Technology

Nondestructive monitoring of annealing and chemical-mechanical planarization behavior using ellipsometry and deep learning

Q. Sun, D. Yang, et al.

Predicting 1, 2 and 3 year emergent referable diabetic retinopathy and maculopathy using deep learning
Medicine and Health

Predicting 1, 2 and 3 year emergent referable diabetic retinopathy and maculopathy using deep learning

P. Nderitu, J. M. N. D. Rio, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny