The paper chase and the big data arms race.
作者信息
Curchoe Carol Lynn
机构信息
CCRM-Orange County, 3501 Jamboree Road, Newport Beach, CA, 92660, USA.
出版信息
J Assist Reprod Genet. 2021 Jul;38(7):1613-1615. doi: 10.1007/s10815-021-02122-3. Epub 2021 Mar 13.
Abstract
摘要
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Artificial intelligence in in vitro fertilization: a computer decision support system for day-to-day management of ovarian stimulation during in vitro fertilization.人工智能在体外受精中的应用：一个计算机决策支持系统，用于体外受精过程中卵巢刺激的日常管理。
Fertil Steril. 2020 Nov;114(5):1026-1031. doi: 10.1016/j.fertnstert.2020.06.006. Epub 2020 Oct 1.
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Performance of a deep learning based neural network in the selection of human blastocysts for implantation.基于深度学习的神经网络在选择人类囊胚进行植入中的性能。
Elife. 2020 Sep 15;9:e55301. doi: 10.7554/eLife.55301.
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Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF.开发一种基于人工智能的评估模型，用于通过体外受精期间光学显微镜拍摄的静态图像预测胚胎活力。
Hum Reprod. 2020 Apr 28;35(4):770-784. doi: 10.1093/humrep/deaa013.
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Predicting pregnancy test results after embryo transfer by image feature extraction and analysis using machine learning.利用机器学习进行图像特征提取和分析，预测胚胎移植后的妊娠试验结果。
Sci Rep. 2020 Mar 10;10(1):4394. doi: 10.1038/s41598-020-61357-9.
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Deep learning as a predictive tool for fetal heart pregnancy following time-lapse incubation and blastocyst transfer.深度学习作为一种预测工具，用于在延时孵育和囊胚转移后预测妊娠的胎儿心脏。
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Feasibility of artificial intelligence for predicting live birth without aneuploidy from a blastocyst image.利用人工智能从囊胚图像预测非整倍体活产的可行性。
Reprod Med Biol. 2019 Feb 19;18(2):204-211. doi: 10.1002/rmb2.12267. eCollection 2019 Apr.
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Prediction of implantation after blastocyst transfer in in vitro fertilization: a machine-learning perspective.体外受精中囊胚移植后着床的预测：机器学习视角。
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