Robotics & Machine Learning Daily News2024,Issue(Nov.18) :12-13.

New Data from University of Toronto Illuminate Research in Machine Learning (Non -invasively predicting euploidy in human blastocysts via quantitative 3D morphol ogy measurement: a retrospective cohort study)

多伦多大学的新数据阐明了机器学习的研究(通过定量三维形态测量非侵入性预测人类囊胚整倍体:回顾性队列研究)

Robotics & Machine Learning Daily News2024,Issue(Nov.18) :12-13.

New Data from University of Toronto Illuminate Research in Machine Learning (Non -invasively predicting euploidy in human blastocysts via quantitative 3D morphol ogy measurement: a retrospective cohort study)

多伦多大学的新数据阐明了机器学习的研究(通过定量三维形态测量非侵入性预测人类囊胚整倍体:回顾性队列研究)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员发布关于人工智能的新报告。根据新闻报道由NewsRx通讯员从多伦多大学发起,研究称:“囊胚形态学”已证实与倍性状态有关。现有的人工智能模型采用人工分级或二维图像作为整倍体预测的输入,这种方法存在主观性观察者和信息丢失,因为二维图像的不完整特征。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on ar tificial intelligence. According to news reportingoriginating from the Universi ty of Toronto by NewsRx correspondents, research stated, “Blastocyst morphologyhas been demonstrated to be associated with ploidy status. Existing artificial i ntelligence models use manual grading or 2D images as the input for euploidy pre diction, which suffer from subjectivity fromobservers and information loss due to incomplete features from 2D images.”

Key words

University of Toronto/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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