• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

关于数字化与人工智能、数据保护、数据交换、数据挖掘——睡眠医学的法律限制/挑战

About Digitalisation and AI, Data Protection, Data Exchange, Data Mining-Legal Constraints/Challenges Concerning Sleep Medicine.

作者信息

Feige Bernd, Benz Fee, Dressle Raphael J, Riemann Dieter

机构信息

Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Freiburg, Germany.

Faculty of Medicine, University of Freiburg, Freiburg, Germany.

出版信息

J Sleep Res. 2025 Oct;34(5):e70044. doi: 10.1111/jsr.70044. Epub 2025 Mar 19.

DOI:10.1111/jsr.70044
PMID:40104922
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12426696/
Abstract

The revolution of artificial intelligence (AI) methods in the scope of the last years has inspired a deluge of use cases but has also caused uncertainty about the actual utility and boundaries of these methods. In this overview, we briefly introduce their main characteristics before focusing on use cases in sleep medicine, discriminating four main areas: Measuring sleep state, advancing diagnostics, advancing research and general advances. We then outline the current European legal framework on AI and the related topic of data sharing.

摘要

近年来,人工智能(AI)方法的变革催生了大量用例,但也引发了人们对这些方法实际效用和边界的不确定性。在本综述中,我们将简要介绍其主要特征,然后重点关注睡眠医学中的用例,区分四个主要领域:测量睡眠状态、推进诊断、推进研究和总体进展。接着,我们将概述当前欧洲关于人工智能的法律框架以及数据共享的相关主题。

相似文献

1
About Digitalisation and AI, Data Protection, Data Exchange, Data Mining-Legal Constraints/Challenges Concerning Sleep Medicine.关于数字化与人工智能、数据保护、数据交换、数据挖掘——睡眠医学的法律限制/挑战
J Sleep Res. 2025 Oct;34(5):e70044. doi: 10.1111/jsr.70044. Epub 2025 Mar 19.
2
Prescription of Controlled Substances: Benefits and Risks管制药品的处方:益处与风险
3
Interventions to improve safe and effective medicines use by consumers: an overview of systematic reviews.改善消费者安全有效用药的干预措施:系统评价概述
Cochrane Database Syst Rev. 2014 Apr 29;2014(4):CD007768. doi: 10.1002/14651858.CD007768.pub3.
4
Challenges and Opportunities for Data Sharing Related to Artificial Intelligence Tools in Health Care in Low- and Middle-Income Countries: Systematic Review and Case Study From Thailand.低收入和中等收入国家医疗保健领域与人工智能工具相关的数据共享面临的挑战与机遇:系统评价及来自泰国的案例研究
J Med Internet Res. 2025 Feb 4;27:e58338. doi: 10.2196/58338.
5
Healthcare workers' informal uses of mobile phones and other mobile devices to support their work: a qualitative evidence synthesis.医护人员非正规使用手机和其他移动设备来支持工作:定性证据综合评价。
Cochrane Database Syst Rev. 2024 Aug 27;8(8):CD015705. doi: 10.1002/14651858.CD015705.pub2.
6
The Use of Artificial Intelligence and Wearable Inertial Measurement Units in Medicine: Systematic Review.人工智能与可穿戴惯性测量单元在医学中的应用:系统评价
JMIR Mhealth Uhealth. 2025 Jan 29;13:e60521. doi: 10.2196/60521.
7
Sexual Harassment and Prevention Training性骚扰与预防培训
8
Diabetic retinopathy screening through artificial intelligence algorithms: A systematic review.基于人工智能算法的糖尿病视网膜病变筛查:系统综述。
Surv Ophthalmol. 2024 Sep-Oct;69(5):707-721. doi: 10.1016/j.survophthal.2024.05.008. Epub 2024 Jun 15.
9
Community engagement for artificial intelligence health research in Africa.非洲人工智能健康研究的社区参与。
Wellcome Open Res. 2025 Mar 20;10:158. doi: 10.12688/wellcomeopenres.23684.1. eCollection 2025.
10
Multi-stakeholder preferences for the use of artificial intelligence in healthcare: A systematic review and thematic analysis.多利益相关方对人工智能在医疗保健中的应用的偏好:系统评价和主题分析。
Soc Sci Med. 2023 Dec;338:116357. doi: 10.1016/j.socscimed.2023.116357. Epub 2023 Nov 4.

本文引用的文献

1
Ensuring medical AI safety: interpretability-driven detection and mitigation of spurious model behavior and associated data.确保医学人工智能安全:基于可解释性的虚假模型行为及相关数据检测与缓解
Mach Learn. 2025;114(9):206. doi: 10.1007/s10994-025-06834-w. Epub 2025 Aug 12.
2
Research Domain Criteria in NIMH Grants Characterized Using Large Language Models.使用大语言模型对美国国立精神卫生研究所(NIMH)资助项目中的研究领域标准进行特征描述。
JAMA Netw Open. 2025 Feb 3;8(2):e2459371. doi: 10.1001/jamanetworkopen.2024.59371.
3
A deep learning-enabled smart garment for accurate and versatile monitoring of sleep conditions in daily life.一种基于深度学习的智能服装,用于在日常生活中准确、多功能地监测睡眠状况。
Proc Natl Acad Sci U S A. 2025 Feb 18;122(7):e2420498122. doi: 10.1073/pnas.2420498122. Epub 2025 Feb 11.
4
New diagnosis in psychiatry: beyond heuristics.精神病学中的新诊断:超越启发法。
Psychol Med. 2025 Feb 6;55:e26. doi: 10.1017/S003329172400223X.
5
A data-driven latent variable approach to validating the research domain criteria framework.一种用于验证研究领域标准框架的数据驱动潜变量方法。
Nat Commun. 2025 Jan 18;16(1):830. doi: 10.1038/s41467-025-55831-z.
6
Long-term effects of attention deficit hyperactivity disorder (ADHD) on social functioning and health care outcomes.注意缺陷多动障碍(ADHD)对社会功能和医疗保健结局的长期影响。
J Psychiatr Res. 2025 Feb;182:212-220. doi: 10.1016/j.jpsychires.2025.01.016. Epub 2025 Jan 8.
7
Exploration of an intrinsically explainable self-attention based model for prototype generation on single-channel EEG sleep stage classification.基于自注意力的可解释性原型生成模型在单通道 EEG 睡眠分期分类中的探索。
Sci Rep. 2024 Nov 11;14(1):27612. doi: 10.1038/s41598-024-79139-y.
8
Sleep diaries and other subjective measures are essential for the assessment of insomnia.睡眠日记和其他主观测量方法对于失眠的评估至关重要。
J Sleep Res. 2025 Feb;34(1):e14313. doi: 10.1111/jsr.14313. Epub 2024 Sep 4.
9
Attention-based CNN-BiLSTM for sleep state classification of spatiotemporal wide-field calcium imaging data.基于注意力机制的卷积神经网络-双向长短时记忆网络在时空宽场钙成像数据睡眠状态分类中的应用。
J Neurosci Methods. 2024 Nov;411:110250. doi: 10.1016/j.jneumeth.2024.110250. Epub 2024 Aug 14.
10
BDNF-TrkB signaling orchestrates the buildup process of local sleep.BDNF-TrkB 信号协调局部睡眠的建立过程。
Cell Rep. 2024 Jul 23;43(7):114500. doi: 10.1016/j.celrep.2024.114500. Epub 2024 Jul 15.