Embryo Ranking Intelligent Classification Algorithm (ERICA) is a deep learning[1]AI software designed to assist embryologists and clinicians during the embryo selection process leading to embryo transfer,[2] a critical step of in vitro fertilisation treatments (IVF).
This AI-based software relies on artificial vision to extract features not identifiable with the use of conventional microscopy.[3] Following feature extraction, ERICA accurately ranks embryos according to their prognosis (defined as euploidy and implantation potential). In this way, ERICA removes the subjectivity inherent to previously existing classifications and, by efficiently assisting clinicians, increases the chances of selecting the one embryo with the best chances to become a baby.[4]
ERICA's algorithms and the EmbryoRanking.com associated software are cloud-based and base their ranking system on predicting individual embryo's genetic status in a non-invasive fashion.[5][6]
^"P-413 - DEEP LEARNING FOR AUTOMATIC DETERMINATION OF BLASTOCYST EMBRYO DEVELOPMENT STAGE". onlineevent.com.
^Chavez-Badiola, Alejandro; Flores-Saiffe Farias, Adolfo; Mendizabal-Ruiz, Gerardo; Garcia-Sanchez, Rodolfo; Drakeley, Andrew J. (September 2019). "Development and preliminary validation of an automated static digital image analysis system utilizing machine learning for blastocyst selection". Fertility and Sterility. 112 (3): e149–e150. doi:10.1016/j.fertnstert.2019.07.511.
^Chavez-Badiola, Alejandro; Flores-Saiffe Farias, Adolfo; Mendizabal-Ruiz, Gerardo; Drakeley, Andrew J.; Garcia-Sánchez, Rodolfo; Zhang, John J. (September 2019). "Artificial vision and machine learning designed to predict PGT-A results". Fertility and Sterility. 112 (3): e231. doi:10.1016/j.fertnstert.2019.07.715.
^Chavez-Badiola, Alejandro; Flores-Saiffe Farias, Adolfo; Mendizabal-Ruiz, Gerardo; Garcia-Sanchez, Rodolfo; Drakeley, Andrew J.; Garcia-Sandoval, Juan Paulo (10 March 2020). "Predicting pregnancy test results after embryo transfer by image feature extraction and analysis using machine learning". Scientific Reports. 10 (1): 4394. Bibcode:2020NatSR..10.4394C. doi:10.1038/s41598-020-61357-9. PMC7064494. PMID 32157183.
^Chavez-Badiola, Alejandro; Mendizabal-Ruiz, Gerardo; Ocegueda-Hernandez, Vladimir; Flores-Saiffe Farias, Adolfo; Drakeley, Andrew J. (September 2019). "Deep learning for automatic determination of blastocyst embryo development stage". Fertility and Sterility. 112 (3): e273. doi:10.1016/j.fertnstert.2019.07.809.
^. www.machinelearning.ai. Archived from the original on 2020-02-01.
embryo, ranking, intelligent, classification, algorithm, erica, deep, learning, software, designed, assist, embryologists, clinicians, during, embryo, selection, process, leading, embryo, transfer, critical, step, vitro, fertilisation, treatments, this, based,. Embryo Ranking Intelligent Classification Algorithm ERICA is a deep learning 1 AI software designed to assist embryologists and clinicians during the embryo selection process leading to embryo transfer 2 a critical step of in vitro fertilisation treatments IVF This AI based software relies on artificial vision to extract features not identifiable with the use of conventional microscopy 3 Following feature extraction ERICA accurately ranks embryos according to their prognosis defined as euploidy and implantation potential In this way ERICA removes the subjectivity inherent to previously existing classifications and by efficiently assisting clinicians increases the chances of selecting the one embryo with the best chances to become a baby 4 ERICA s algorithms and the EmbryoRanking com associated software are cloud based and base their ranking system on predicting individual embryo s genetic status in a non invasive fashion 5 6 See also editEmbryo selection In vitro fertilisation and embryo selectionReferences edit P 413 DEEP LEARNING FOR AUTOMATIC DETERMINATION OF BLASTOCYST EMBRYO DEVELOPMENT STAGE onlineevent com Chavez Badiola Alejandro Flores Saiffe Farias Adolfo Mendizabal Ruiz Gerardo Garcia Sanchez Rodolfo Drakeley Andrew J September 2019 Development and preliminary validation of an automated static digital image analysis system utilizing machine learning for blastocyst selection Fertility and Sterility 112 3 e149 e150 doi 10 1016 j fertnstert 2019 07 511 Chavez Badiola Alejandro Flores Saiffe Farias Adolfo Mendizabal Ruiz Gerardo Drakeley Andrew J Garcia Sanchez Rodolfo Zhang John J September 2019 Artificial vision and machine learning designed to predict PGT A results Fertility and Sterility 112 3 e231 doi 10 1016 j fertnstert 2019 07 715 Chavez Badiola Alejandro Flores Saiffe Farias Adolfo Mendizabal Ruiz Gerardo Garcia Sanchez Rodolfo Drakeley Andrew J Garcia Sandoval Juan Paulo 10 March 2020 Predicting pregnancy test results after embryo transfer by image feature extraction and analysis using machine learning Scientific Reports 10 1 4394 Bibcode 2020NatSR 10 4394C doi 10 1038 s41598 020 61357 9 PMC 7064494 PMID 32157183 Chavez Badiola Alejandro Mendizabal Ruiz Gerardo Ocegueda Hernandez Vladimir Flores Saiffe Farias Adolfo Drakeley Andrew J September 2019 Deep learning for automatic determination of blastocyst embryo development stage Fertility and Sterility 112 3 e273 doi 10 1016 j fertnstert 2019 07 809 Presenting Erica an artificial intelligence clinical assistant for embryo ranking Machine Learning www machinelearning ai Archived from the original on 2020 02 01 nbsp This human reproduction article is a stub You can help Wikipedia by expanding it vte Retrieved from https en wikipedia org w index php title Embryo Ranking Intelligent Classification Algorithm amp oldid 1086761360, wikipedia, wiki, book, books, library,
