Selection of preimplantation embryos using time-lapse microscopy in in vitro fertilization: State of the technology and future directions

2018 ◽  
Vol 110 (8) ◽  
pp. 648-653 ◽  
Author(s):  
Belén Aparicio-Ruiz ◽  
Laura Romany ◽  
Marcos Meseguer
Keyword(s):  
In Vitro Fertilization ◽  
Time Lapse ◽  
Preimplantation Embryos ◽  
Future Directions ◽  
Vitro Fertilization ◽  
Time Lapse Microscopy ◽  
Selection Of

scholarly journals Solving the "right" problems for effective machine learning driven in vitro fertilization

2021 ◽  
Author(s):  
Itay Erlich ◽  
Assaf Ben-Meir ◽  
Iris Har-Vardi ◽  
James A Grifo ◽  
Assaf Zaritsky
Keyword(s):  
Machine Learning ◽  
In Vitro Fertilization ◽  
Clinical Factors ◽  
Vitro Fertilization ◽  
Data Intensive ◽  
Live Embryo ◽  
The Right ◽  
Visual Properties ◽  
Selection Of

Automated live embryo imaging has transformed in-vitro fertilization (IVF) into a data-intensive field. Unlike clinicians who rank embryos from the same IVF cycle cohort based on the embryos visual quality and determine how many embryos to transfer based on clinical factors, machine learning solutions usually combine these steps by optimizing for implantation prediction and using the same model for ranking the embryos within a cohort. Here we establish that this strategy can lead to sub-optimal selection of embryos. We reveal that despite enhancing implantation prediction, inclusion of clinical properties hampers ranking. Moreover, we find that ambiguous labels of failed implantations, due to either low quality embryos or poor clinical factors, confound both the optimal ranking and even implantation prediction. To overcome these limitations, we propose conceptual and practical steps to enhance machine-learning driven IVF solutions. These consist of separating the optimizing of implantation from ranking by focusing on visual properties for ranking, and reducing label ambiguity.

Selection of Reference miRNAs for Relative Quantification in Buffalo (Bubalus bubalis) Blastocysts Produced by Hand-Made Cloning and In Vitro Fertilization

2019 ◽  
Vol 21 (4) ◽  
pp. 200-209 ◽  
Author(s):  
Swati Viviyan Lagah ◽  
Tanushri Jerath Sood ◽  
Prabhat Palta ◽  
Manishi Mukesh ◽  
Manmohan Singh Chauhan ◽  
...  
Keyword(s):  
In Vitro Fertilization ◽  
Bubalus Bubalis ◽  
Relative Quantification ◽  
Vitro Fertilization ◽  
Selection Of ◽  
Reference Mirnas

scholarly journals Selection of first in vitro fertilization (IVF) cycle stimulation protocol for good prognosis patients: GnRH antagonist vs. agonist protocols

2007 ◽  
Vol 88 ◽  
pp. S152
Author(s):  
E.B. Johnston-MacAnanny ◽  
A.J. DiLuigi ◽  
L.L. Engmann ◽  
D.B. Maier ◽  
C.A. Benadiva ◽  
...  
Keyword(s):  
In Vitro Fertilization ◽  
Gnrh Antagonist ◽  
Good Prognosis ◽  
Stimulation Protocol ◽  
Vitro Fertilization ◽  
Selection Of
Sign in / Sign up

Export Citation Format

Share Document