儿童阻塞性睡眠呼吸暂停进展:认知影响与AI在精准医学中的作用 Table 1

儿童阻塞性睡眠呼吸暂停认知影响及AI精准医学文献计量分析Table 1,涵盖1983–2025年WoSCC/Scopus共1,610篇研究。

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表格pediatric obstructive sleep apneacognitionbibliometric analysisartificial intelligenceprecision medicine
Table 1_Advancements in pediatric obstructive sleep apnea: cognitive implications and the role of AI in precision medicine.docx

基本信息

模态
表格
大小
0.000017808 GB
许可
CC BY 4.0
创建/更新时间
2026-10-17
版本
v1

资源简介

儿童阻塞性睡眠呼吸暂停进展:认知影响与AI在精准医学中的作用 Table 1

【一句话概览】

本数据集是 figshare 公开的结构化表格数据集,收录 1 个文件、合计 17.81 KB,主题涵盖 pediatric obstructive sleep apnea、cognition、bibliometric analysis、artificial intelligence、precision medicine,可用于统计建模、特征工程与队列分析,CC BY 4.0 许可开放获取。

【数据集背景】

本数据集源站标题为《Table 1_Advancements in pediatric obstructive sleep apnea: cognitive implications and the role of AI in precision medicine.docx》。配套论文《A Convolutional Neural Network Architecture to Enhance Oximetry Ability to Diagnose Pediatric Obstructive Sleep Apnea》发表于 IEEE Journal of Biomedical and Health Informatics(2021),DOI:10.1109/jbhi.2020.3048901。源站首次发布:2025-11-21。

【数据内容】

源站原始描述:BackgroundObstructive sleep apnea (OSA) in children is linked to cognitive impairment, which is further aggravated by fragmented sleep, intermittent hypoxia, and comorbid attention deficit hyperactivity disorder (ADHD), often resulting in poor academic performance, behavioral problems, and delayed neurodevelopment. MethodsA bibliometric and scientometric analysis was conducted using Web of Science Core Collection (WoSCC) and Scopus databases (1983–2025). After exclusion of non-article records an…

【数据结构与技术规格】

文件数 1 个,合计 17.81 KB。Table 1_Advancements in pediatric obstructive sleep apnea: cognitive implications and the role of AI in precision medicine.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,17.81 KB。数据集 DOI:10.3389/fmed.2025.1704504.s002。

【主题与分类】

源站学科分类:Foetal Development and Medicine。主题标签:pediatric obstructive sleep apnea、cognition、bibliometric analysis、artificial intelligence、precision medicine。

【适用方向】

结构化表格数据可直接用于统计建模、特征工程与队列分析。

【获取与许可】

源站页面:https://frontiersin.figshare.com/articles/dataset/Table_1_Advancements_in_pediatric_obstructive_sleep_apnea_cognitive_implications_and_the_role_of_AI_in_precision_medicine_docx/30673364

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Zhao, Bomeng; Fan, Haixia; Niu, Huiyan; Li, Yan; Deng, Shudan; Zhai, Lu; et al. (2025). Table 1_Advancements in pediatric obstructive sleep apnea: cognitive implications and the role of AI in precision medicine.docx. Frontiers. Dataset

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下载信息

注册下载

需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。

暂未开放

公开下载

无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。

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有偿下载

公开数据集受托下载与技术交付服务。

提供高速下载与技术交付服务(收技术服务费,非数据销售)

暂未开放

当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。

使用方式

数据集获取(Figshare)

命令行下载

curl -L -o "Table 1_Advancements in pediatric obstructive sleep apnea: cognitive implications and the role of AI in precision medicine.docx" "https://ndownloader.figshare.com/files/59745284"

文件清单

  • Table 1_Advancements in pediatric obstructive sleep apnea: cognitive implications and the role of AI in precision medicine.docx(17.81 KB)

文件总体积 17.81 KB(源站 API 实测)。

数据加载示例(图像类)

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

BackgroundObstructive sleep apnea (OSA) in children is linked to cognitive impairment, which is further aggravated by fragmented sleep, intermittent hypoxia, and comorbid attention deficit hyperactivity disorder (ADHD), often resulting in poor academic performance, behavioral problems, and delayed neurodevelopment.
MethodsA bibliometric and scientometric analysis was conducted using Web of Science Core Collection (WoSCC) and Scopus databases (1983–2025). After exclusion of non-article records and duplicates, 1,610 studies were included. CiteSpace, VOSviewer, and the R-based Bibliometrix package were employed to analyze publication trends, authorship, institutional collaborations, co-citations, and keyword evolution.
ResultsSince 2010, scholarly attention to pediatric obstructive sleep apnea and its cognitive implications has grown rapidly, with research output increasing at an annual rate of 11.96%. The United States, China, and several European countries stand out as major contributors, both in terms of publications and international collaboration. Prominent academic centers—such as Harvard University, the University of Michigan, and the University of Chicago—serve as key institutional hubs. Among the most influential contributors to the field are David Gozal and Leila Kheirandish-Gozal, while leading journals include Sleep Medicine and the Journal of Clinical Sleep Medicine. Keyword mapping highlights the central focus on “obstructive sleep apnea,” “children,” and “sleep-disordered breathing,” alongside diagnostic and treatment terms such as “polysomnography” and “adenotonsillectomy.” Notably, there is growing emphasis on cognitive and behavioral aspects, including “cognition,” “behavior,” and “ADHD,” as well as comorbidities like “obesity” and “Down syndrome.” Recent clusters underscore advances in artificial intelligence (AI) and machine learning (ML) based models using oximetry, electrocardiogram (ECG), and acoustic data, enabling early detection and supporting precision medicine approaches.
ConclusionThe relationship between pediatric obstructive sleep apnea and neurocognitive development has gained significant attention, with recent research focusing on c

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fmed.2025.1704504.s002(source: https://frontiersin.figshare.com/articles/dataset/Table_1_Advancements_in_pediatric_obstructive_sleep_apnea_cognitive_implications_and_the_role_of_AI_in_precision_medicine_docx/30673364)。

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依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。

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