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

Extraction: Advanced Methods00:56

Extraction: Advanced Methods

526
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
526
Methods of Classification and Identification01:28

Methods of Classification and Identification

183
Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
183
Peptide Identification Using Tandem Mass Spectrometry01:33

Peptide Identification Using Tandem Mass Spectrometry

6.8K
Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
6.8K

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

Evaluating Prompt Strategies for LLM-Based De-Identification of German Discharge Letters: A Feasibility Study Using GraSCCo.

Studies in health technology and informatics·2026
Same author

Selecting medical research data platforms for translational biomedical research: a five-tier overview and requirement-weighted assessment framework.

Frontiers in digital health·2026
Same author

Circtools 2.0: a comprehensive framework for enhanced circular RNA bioinformatics.

BMC bioinformatics·2026
Same author

A distributed analysis approach for pharmacovigilance data from electronic medical records in German university hospitals: the POLAR_MI ETL Pipeline.

BMC medical informatics and decision making·2026
Same author

Language Models for Automatic Clinical Coding in Veterinary Texts: Experimental Results.

Studies in health technology and informatics·2026
Same author

GFO-Light: A Simplified Top-Level Ontology - Introduction and Biomedical Case Studies.

Studies in health technology and informatics·2026
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026
查看所有相关文章

相关实验视频

Updated: Sep 9, 2025

Isolation of Mandibular Gland Reservoir Contents from Bornean 'Exploding Ants' Formicidae for Volatilome Analysis by GC-MS and MetaboliteDetector
11:07

Isolation of Mandibular Gland Reservoir Contents from Bornean 'Exploding Ants' Formicidae for Volatilome Analysis by GC-MS and MetaboliteDetector

Published on: August 26, 2018

8.9K

行动中的GeMTeX去识别:学到的教训和魔鬼的细节

Christina Lohr1,2, Jakob Faller3,2, Andrea Riedel3,4,2

  • 1Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany.

Studies in health technology and informatics
|September 3, 2025
PubMed
概括
此摘要是机器生成的。

在GeMTeX项目中创建了GraSCCoPHI,这是一个非标识的德国临床报告库. 无法预见的识别挑战遵循帕雷托原则,大多数问题都源于一小部分注释.

关键词:
删除标识自然语言处理隐私问题

更多相关视频

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
05:35

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

3.8K
Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project
10:19

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

17.6K

相关实验视频

Last Updated: Sep 9, 2025

Isolation of Mandibular Gland Reservoir Contents from Bornean 'Exploding Ants' Formicidae for Volatilome Analysis by GC-MS and MetaboliteDetector
11:07

Isolation of Mandibular Gland Reservoir Contents from Bornean 'Exploding Ants' Formicidae for Volatilome Analysis by GC-MS and MetaboliteDetector

Published on: August 26, 2018

8.9K
An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
05:35

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome

Published on: September 20, 2022

3.8K
Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project
10:19

Transcriptomic Analysis of C. elegans RNA Sequencing Data Through the Tuxedo Suite on the Galaxy Project

Published on: April 8, 2017

17.6K

科学领域:

  • 医疗信息学
  • 自然语言处理
  • 数据隐私

背景情况:

  • GeMTeX项目于2024年启动了德国临床报告的大规模去标识活动.
  • 这项试点研究的结果是GraSCCoPHI,这是德国第一个非识别的合成排放总结的黄金标准.

研究的目的:

  • 描述 GeMTeX 脱标工作流程,包括注释管理和培训.
  • 介绍第一年的进展,挑战和数量洞察力.

主要方法:

  • 开发并管理一个注释工具.
  • 组建和训练注释组.
  • 通过代过程演变的非识别指南.

主要成果:

  • 该项目在德国四个州的六个医院中面临着未知的挑战.
  • 分析了一份临时文件集 (9,000份文件,2000万个令牌) 显示了每份文件的平均可识别信息.
  • 识别了混因素,并从去识别过程中吸取了关键教训.

结论:

  • 在非识别注释中出现的意外障碍往往遵循帕雷托原则.
  • 一个很小的百分比的注释问题占大多数未预见的挑战.