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

Pulmonary Tuberculosis I01:29

Pulmonary Tuberculosis I

Tuberculosis, often called TB, is a contagious illness primarily caused by Mycobacterium tuberculosis. It mainly affects the lung parenchyma but can also impact other body parts.
Causative Organism
The primary infectious agent causing tuberculosis is Mycobacterium tuberculosis, a slow-growing, acid-fast, aerobic rod that exhibits sensitivity to heat and ultraviolet light. Instances of Mycobacterium bovis and Mycobacterium avium contributing to the development of TB infection are rare.
Mode of...
Pulmonary Tuberculosis II01:28

Pulmonary Tuberculosis II

Tuberculosis, or TB, is a bacterial infectious disease caused by Mycobacterium tuberculosis. While its primary impact is on the lungs, leading to pulmonary tuberculosis, it can also affect various other organs, a condition referred to as extrapulmonary tuberculosis.
Here is a detailed explanation of its pathophysiology:
Transmission: The process begins when a person inhales droplet nuclei containing M. tuberculosis. These are typically released into the air when an individual with pulmonary or...
Pulmonary Tuberculosis III01:31

Pulmonary Tuberculosis III

Tuberculosis (TB) is a contagious infection primarily affecting the lung parenchyma but which can also affect other body parts. TB can be classified based on disease development, presentation, and the affected anatomical site.
The first classification is based on the development of the disease, and it includes the following categories:
Pulmonary Tuberculosis IV01:26

Pulmonary Tuberculosis IV

Tuberculosis, more commonly referred to as TB, is an infectious disease stemming from Mycobacterium tuberculosis. While it primarily impacts the lungs, TB can also affect other body areas. Given its severity and global impact, timely and accurate diagnosis is crucial for controlling its spread and improving patient outcomes.
Several diagnostic approaches are used to detect TB. The conventional method is the Tuberculin Skin Test (TST), also known as the Mantoux test. However, this method has...
Pulmonary Tuberculosis V01:28

Pulmonary Tuberculosis V

Medical management of tuberculosis (TB) patients involves a comprehensive approach that includes diagnosis, treatment, and monitoring. The specific strategies can vary depending on the type of tuberculosis (latent or active), the patient's overall health status, and other considerations.
Latent tuberculosis infection occurs when TB bacteria are present in a person's body, but are not causing illness or symptoms. It is not contagious, and preventive treatment is crucial to avoid the progression...

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

Noninvasive and minimally invasive approaches for acute and chronic stress assessment in dairy cattle.

Journal of dairy science·2026
Same author

Conceptual qualitative system dynamics model for simulation of perceived workload, stress and performance from industrial work content.

PloS one·2026
Same author

Prognostic and predictive factors of immune checkpoint inhibitor therapy in urinary bladder cancer.

Pathology oncology research : POR·2026
Same author

The value of social robots supporting informal care: a discrete choice experiment among informal caregivers.

The European journal of health economics : HEPAC : health economics in prevention and care·2026
Same author

Stochastic virtual population in type 1 diabetes.

PloS one·2026
Same author

Improving the value of population health data for health policy and decision-making using machine learning algorithms in EQ-5D-5L index estimation.

Scientific reports·2026
Same journal

Electro-osmotic metachronal cilia transport of viscoelastic blood infused with penta-hybrid nanoparticles in an oviduct: Analytical and neural network modeling.

Computers in biology and medicine·2026
Same journal

sEEGnal: an automated EEG preprocessing pipeline evaluated against expert-driven preprocessing.

Computers in biology and medicine·2026
Same journal

Corrigendum to "Integrating experimental biology, computational methods, and artificial Intelligence in anticancer drug discovery: Bridging the translational Gap" [Comput. Biol. Med. 213 (2026) 111832].

Computers in biology and medicine·2026
Same journal

Organ dose optimization for a point-of-care forearm X-ray photon-counting CT.

Computers in biology and medicine·2026
Same journal

Physics-guided transformation of breathomic feature spaces into disease-specific representations for respiratory disease classification.

Computers in biology and medicine·2026
Same journal

An AI-driven deep learning pipeline for taxonomic classification and biodiversity assessment of deep-sea environmental DNA.

Computers in biology and medicine·2026
查看所有相关文章

相关实验视频

Updated: May 22, 2026

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification
07:47

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification

Published on: February 14, 2018

11.2K

用深度学习和惯性测量单元传感器进行个性化食品消费检测.

Lehel Dénes-Fazakas1, Barbara Simon2, Ádám Hartvég2

  • 1Physiological Controls Research Center, University Research and Innovation Center, Obuda University, Bécsi út 96/b, Budapest, 1034, Hungary; Biomatics and Applied Artificial Intelligence Institute, John von Neumann Faculty of Informatics, Obuda University, Bécsi út 96/b, Budapest, 1034, Hungary; Doctoral School of Applied Informatics and Applied Mathematics, Obuda University, Bécsi út 96/b, Budapest, 1034, Hungary.

Computers in biology and medicine
|September 26, 2024
PubMed
概括
此摘要是机器生成的。

一个新的深度学习模型准确地检测了糖尿病管理的碳水化合物摄入量,这对于人工胰腺用户至关重要. 这项技术通过监测每天的饮食和碳水化合物消耗,有助于精确的胰岛素输送.

关键词:
深度学习是一种深度学习.糖尿病是一种糖尿病.用手势检测检测的手势检测.个性化模型个性化模型经常出现的神经网络.

更多相关视频

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.0K
Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method
06:21

Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method

Published on: February 19, 2021

5.7K

相关实验视频

Last Updated: May 22, 2026

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification
07:47

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification

Published on: February 14, 2018

11.2K
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.0K
Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method
06:21

Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method

Published on: February 19, 2021

5.7K

科学领域:

  • 生物医学工程 生物医学工程
  • 医疗保健中的人工智能
  • 糖尿病 技术 技术

背景情况:

  • 精确的碳水化合物计数对于糖尿病管理至关重要,特别是对于使用人工胰腺系统的人来说.
  • 手动碳水化合物跟踪经常被忽视,影响血糖控制和胰岛素剂量.
  • 人工胰腺系统依靠精确的碳水化合物摄入数据来有效激活胰岛素.

研究的目的:

  • 开发和验证一个个性化的深度学习模型,用于准确检测碳水化合物摄入量.
  • 通过精确的食监测,改善人工胰腺系统中自动胰岛素的输送.
  • 为了应对糖尿病管理中手动碳水化合物跟踪不一致的挑战.

主要方法:

  • 利用来自惯性测量单元 (IMU) 的公开可用的数据集,采用加速度计和陀螺仪数据,采用 15 Hz 的频率.
  • 预处理了传感器数据,并采用了具有长短期记忆 (LSTM) 层的循环神经网络架构,用于针对患者量身定制的建模.
  • 使用F1得分和混矩阵分析等指标评估模型性能.

主要成果:

  • 深度学习模型获得了0.99的F1中位数,在碳水化合物摄入量检测方面表现出高准确性.
  • 该模型的性能始终在90%以上,大多数结果在98%至99%之间.
  • 混矩阵分析显示了最小的差异 (6秒),平均预测延迟时间为5.5秒.

结论:

  • 开发的个性化深度学习模型准确地检测碳水化合物摄入量,为糖尿病管理提供了重大进展.
  • 经常性神经网络,特别是LSTM,大大提高了这个任务的解决问题的能力.
  • 未来的工作可能涉及变压器网络和更短的时间窗口,以进一步提高响应能力和准确性,建议采集多天的数据.