Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A highly accurate framework for estimating eye muscle area and backfat thickness of pigs in vivo using deep learning.

Meat science·2026
Same author

Autologous distal femoral condyle graft for patellar reconstruction during TKA in posttraumatic ankylosis: a case report.

Frontiers in surgery·2026
Same author

A multi-center clinical evaluation on first-in-class ROP-based IGRA for tuberculosis diagnosis.

iScience·2026
Same author

Identification of ROS-Related Gene TNFSF13B as a Diagnostic Biomarker in Tuberculosis: Insights from WGCNA.

Infection and drug resistance·2026
Same author

Cortical thinning with increasing OSA severity stages in adult comorbid insomnia and sleep apnea and its relevance for respiration measures.

Scientific reports·2026
Same author

Comparative extracellular and intracellular anti-Mycobacterium tuberculosis activity of three tanshinones from Salvia miltiorrhiza and oral cryptotanshinone efficacy in mice.

Naunyn-Schmiedeberg's archives of pharmacology·2026

相关实验视频

Updated: May 24, 2025

A Modified Sonographic Algorithm for Image Acquisition in Life-Threatening Emergencies in the Critically Ill Newborn
11:27

A Modified Sonographic Algorithm for Image Acquisition in Life-Threatening Emergencies in the Critically Ill Newborn

Published on: April 7, 2023

6.1K

基于摄像头的婴儿窒息风险检测通过文本到图像生成来保护睡眠安全.

Dongmin Huang, Chuchu Liao, Jingyun Mai

    IEEE journal of biomedical and health informatics
    |March 4, 2025
    PubMed
    概括
    此摘要是机器生成的。

    这项研究使用人工智能生成的婴儿图像来检测窒息风险,达到90%以上的准确性. 这种方法克服了数据稀缺性,通过先进的摄像头监控提高了婴儿睡眠安全.

    更多相关视频

    Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
    09:24

    Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable

    Published on: May 17, 2024

    1.3K
    Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System
    05:10

    Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

    Published on: March 17, 2023

    2.6K

    相关实验视频

    Last Updated: May 24, 2025

    A Modified Sonographic Algorithm for Image Acquisition in Life-Threatening Emergencies in the Critically Ill Newborn
    11:27

    A Modified Sonographic Algorithm for Image Acquisition in Life-Threatening Emergencies in the Critically Ill Newborn

    Published on: April 7, 2023

    6.1K
    Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
    09:24

    Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable

    Published on: May 17, 2024

    1.3K
    Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System
    05:10

    Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

    Published on: March 17, 2023

    2.6K

    科学领域:

    • 医疗保健中的人工智能
    • 婴儿睡眠安全监测 婴儿睡眠安全监测
    • 计算机视觉用于医疗应用.

    背景情况:

    • 目前的婴儿监测主要使用生理数据,忽视了用于窒息检测的语义分析.
    • 获取婴儿窒息风险模型的标记数据是一个重大的现实挑战.
    • 睡眠期间的口鼻腔封闭对婴儿安全构成重大风险.

    研究的目的:

    • 利用人工智能生成的数据开发一个强大的婴儿窒息风险检测模型.
    • 为了解决医疗保健AI应用中标记数据的稀缺问题.
    • 通过先进的基于摄像头的监控,增强婴儿睡眠安全.

    主要方法:

    • 利用文本到图像的扩散模型来生成各种婴儿图像与口腔鼻腔封闭.
    • 从事自主和半监督学习,从未标记的数据中提取语义信息.
    • 进行了22名新生儿病患者的临床试验,以验证模型的性能.

    主要成果:

    • 在25000张生成图像上训练的模型实现了>90%的准确性,回忆和F1分数.
    • 使用超过9万张标记在线图像的传统方法.
    • 证明了使用合成数据进行可靠的窒息风险检测的可行性.

    结论:

    • 利用文本到图像生成的数据是基于摄像机的婴儿窒息风险检测的可行策略.
    • 这种人工智能方法显著提高了婴儿睡眠安全.
    • 突出了基于文本的大规模模型的潜力,以克服医疗保健人工智能中的人类数据稀缺性.