Machine learning for prediction of euploidy in human embryos: in search of the best-performing model and predictive features
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Machine learning for prediction of euploidy in human embryos: in search of the best-performing model and predictive features
Authors
Keywords
-
Journal
FERTILITY AND STERILITY
Volume -, Issue -, Pages -
Publisher
Elsevier BV
Online
2022-01-20
DOI
10.1016/j.fertnstert.2021.11.029
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Minimally Invasive Cell-Free Human Embryo Aneuploidy Testing (miPGT-A) Utilizing Combined Spent Embryo Culture Medium and Blastocoel Fluid –Towards Development of a Clinical Assay
- (2020) Valeriy Kuznyetsov et al. Scientific Reports
- Embryo Ranking Intelligent Classification Algorithm (ERICA): artificial intelligence clinical assistant predicting embryo ploidy and implantation
- (2020) Alejandro Chavez-Badiola et al. REPRODUCTIVE BIOMEDICINE ONLINE
- Novel and conventional embryo parameters as input data for artificial neural networks: an artificial intelligence model applied for prediction of the implantation potential
- (2020) Lorena Bori et al. FERTILITY AND STERILITY
- NONINVASIVE DETECTION OF BLASTOCYST PLOIDY (EUPLOID VS. ANEUPLOID) USING ARTIFICIAL INTELLIGENCE (AI) WITH DEEP LEARNING METHODS
- (2020) Josue Barnes et al. FERTILITY AND STERILITY
- Prediction of implantation after blastocyst transfer in in vitro fertilization: a machine-learning perspective
- (2019) Celine Blank et al. FERTILITY AND STERILITY
- Computational prediction of implantation outcome after embryo transfer
- (2019) Behnaz Raef et al. Health Informatics Journal
- Can time-lapse parameters predict embryo ploidy? A systematic review
- (2018) Arnaud Reignier et al. REPRODUCTIVE BIOMEDICINE ONLINE
- Assessment of embryo morphology and developmental dynamics by time-lapse microscopy: is there a relation to implantation and ploidy?
- (2017) Nikica Zaninovic et al. FERTILITY AND STERILITY
- Correlation between aneuploidy, standard morphology evaluation and morphokinetic development in 1730 biopsied blastocysts: a consecutive case series study
- (2016) Maria Giulia Minasi et al. HUMAN REPRODUCTION
- Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View
- (2016) Wei Luo et al. JOURNAL OF MEDICAL INTERNET RESEARCH
- Noninvasive chromosome screening of human embryos by genome sequencing of embryo culture medium for in vitro fertilization
- (2016) Juanjuan Xu et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- A predictive model for blastocyst formation based on morphokinetic parameters in time-lapse monitoring of embryo development
- (2015) Robert Milewski et al. JOURNAL OF ASSISTED REPRODUCTION AND GENETICS
- Proposed guidelines on the nomenclature and annotation of dynamic human embryo monitoring by a time-lapse user group
- (2014) H. Nadir Ciray et al. HUMAN REPRODUCTION
- Predictive Modeling of Implantation Outcome in an In Vitro Fertilization Setting
- (2014) Asli Uyar et al. MEDICAL DECISION MAKING
- Morphokinetics and embryo aneuploidy: has time come or not yet?
- (2013) Markus Montag REPRODUCTIVE BIOMEDICINE ONLINE
- Cytogenetic analysis of human blastocysts with the use of FISH, CGH and aCGH: scientific data and technical evaluation
- (2010) E. Fragouli et al. HUMAN REPRODUCTION
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started