• 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

相似文献

1
A short report on ADHD detection using convolutional neural networks.关于使用卷积神经网络进行注意力缺陷多动障碍检测的简短报告。
Front Psychiatry. 2024 Sep 5;15:1426155. doi: 10.3389/fpsyt.2024.1426155. eCollection 2024.
2
Neurological state changes indicative of ADHD in children learned via EEG-based LSTM networks.基于 EEG 的 LSTM 网络学习提示儿童注意缺陷多动障碍的神经状态变化。
J Neural Eng. 2022 Feb 10;19(1). doi: 10.1088/1741-2552/ac4f07.
3
Classification of attention deficit/hyperactivity disorder based on EEG signals using a EEG-Transformer model.基于 EEG-Transformer 模型的脑电信号注意力缺陷多动障碍分类。
J Neural Eng. 2023 Sep 21;20(5). doi: 10.1088/1741-2552/acf7f5.
4
The Hybrid Deep Learning Model for Identification of Attention-Deficit/Hyperactivity Disorder Using EEG.基于 EEG 的注意缺陷多动障碍混合深度学习模型
Clin EEG Neurosci. 2024 Jan;55(1):22-33. doi: 10.1177/15500594231193511. Epub 2023 Sep 8.
5
Deep Learning Enabled Diagnosis of Children's ADHD Based on the Big Data of Video Screen Long-Range EEG.基于视频屏幕长程 EEG 大数据的深度学习辅助儿童 ADHD 诊断。
J Healthc Eng. 2022 Apr 4;2022:5222136. doi: 10.1155/2022/5222136. eCollection 2022.
6
[Study of attention deficit/hyperactivity disorder classification based on convolutional neural networks].基于卷积神经网络的注意力缺陷/多动障碍分类研究
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2017 Feb;34(1):99-105. doi: 10.7507/1001-5515.201606058.
7
Diagnose ADHD disorder in children using convolutional neural network based on continuous mental task EEG.基于连续心理任务脑电图，使用卷积神经网络诊断儿童注意力缺陷多动障碍。
Comput Methods Programs Biomed. 2020 Dec;197:105738. doi: 10.1016/j.cmpb.2020.105738. Epub 2020 Sep 6.
8
Machine Learning Techniques for the Diagnosis of Attention-Deficit/Hyperactivity Disorder from Magnetic Resonance Imaging: A Concise Review.机器学习技术在磁共振成像中对注意缺陷多动障碍的诊断：简明综述。
Neurol India. 2021 Nov-Dec;69(6):1518-1523. doi: 10.4103/0028-3886.333520.
9
Attention Deficit Hyperactivity Disorder Classification Based on Deep Learning.基于深度学习的注意力缺陷多动障碍分类
IEEE/ACM Trans Comput Biol Bioinform. 2023 Mar-Apr;20(2):1581-1586. doi: 10.1109/TCBB.2022.3170527. Epub 2023 Apr 3.
10
Deep Learning Convolutional Neural Networks Discriminate Adult ADHD From Healthy Individuals on the Basis of Event-Related Spectral EEG.深度学习卷积神经网络基于事件相关频谱脑电图区分成人注意力缺陷多动障碍患者与健康个体。
Front Neurosci. 2020 Apr 9;14:251. doi: 10.3389/fnins.2020.00251. eCollection 2020.

本文引用的文献

1
Adaptive spatial-temporal neural network for ADHD identification using functional fMRI.基于功能磁共振成像的用于注意力缺陷多动障碍识别的自适应时空神经网络
Front Neurosci. 2024 May 30;18:1394234. doi: 10.3389/fnins.2024.1394234. eCollection 2024.
2
Gabor filter-based statistical features for ADHD detection.基于Gabor滤波器的统计特征用于注意缺陷多动障碍的检测。
Front Hum Neurosci. 2024 Apr 10;18:1369862. doi: 10.3389/fnhum.2024.1369862. eCollection 2024.
3
Structural or/and functional MRI-based machine learning techniques for attention-deficit/hyperactivity disorder diagnosis: A systematic review and meta-analysis.基于结构和/或功能磁共振成像的机器学习技术在注意缺陷多动障碍诊断中的应用：系统评价和荟萃分析。
J Affect Disord. 2024 Jun 15;355:459-469. doi: 10.1016/j.jad.2024.03.111. Epub 2024 Apr 3.
4
Tools for the Diagnosis of ADHD in Children and Adolescents: A Systematic Review.工具用于诊断 ADHD 儿童和青少年：系统评价。
Pediatrics. 2024 Apr 1;153(4). doi: 10.1542/peds.2024-065854.
5
A Class Activation Map-Based Interpretable Transfer Learning Model for Automated Detection of ADHD from fMRI Data.一种基于类激活映射的可解释迁移学习模型，用于从功能磁共振成像数据中自动检测注意缺陷多动障碍
Clin EEG Neurosci. 2023 Mar;54(2):151-159. doi: 10.1177/15500594221122699. Epub 2022 Sep 1.
6
Attention Deficit Hyperactivity Disorder Classification Based on Deep Learning.基于深度学习的注意力缺陷多动障碍分类
IEEE/ACM Trans Comput Biol Bioinform. 2023 Mar-Apr;20(2):1581-1586. doi: 10.1109/TCBB.2022.3170527. Epub 2023 Apr 3.
7
Neuroimaging in attention-deficit/hyperactivity disorder.注意缺陷多动障碍的神经影像学。
Curr Opin Psychiatry. 2021 Mar 1;34(2):105-111. doi: 10.1097/YCO.0000000000000669.
8
Deep Spatio-Temporal Representation and Ensemble Classification for Attention Deficit/Hyperactivity Disorder.深度时空表示与集成分类在注意缺陷多动障碍中的应用。
IEEE Trans Neural Syst Rehabil Eng. 2021;29:1-10. doi: 10.1109/TNSRE.2020.3019063. Epub 2021 Feb 25.
9
Deep Learning Convolutional Neural Networks Discriminate Adult ADHD From Healthy Individuals on the Basis of Event-Related Spectral EEG.深度学习卷积神经网络基于事件相关频谱脑电图区分成人注意力缺陷多动障碍患者与健康个体。
Front Neurosci. 2020 Apr 9;14:251. doi: 10.3389/fnins.2020.00251. eCollection 2020.

A short report on ADHD detection using convolutional neural networks.

作者信息

Kulkarni Vikram, Nemade Bhushankumar, Patel Shreyaskumar, Patel Keyur, Velpula Srikanth

机构信息

Department of Information Technology, Mukesh Patel School of Technology Management & Engineering, SVKM's NMIMS, Mumbai, Maharashtra, India.

Department of CSE, Shri L R Tiwari College of Engineering, Mumbai, Maharashtra, India.

出版信息

Front Psychiatry. 2024 Sep 5;15:1426155. doi: 10.3389/fpsyt.2024.1426155. eCollection 2024.

DOI:10.3389/fpsyt.2024.1426155
PMID:39301220
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11410607/
Abstract
摘要