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

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

565
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
565

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 authorSame journal

Evaluating a custom GPT assistant for critical appraisal of biological variation studies by the BIVAC.

Clinical chemistry and laboratory medicine·2026
Same author

Age- and Sex-Specific Reference Intervals for TSH, FT4, and FT3 Derived from the Turkish Multi-Center Cohort.

Diagnostics (Basel, Switzerland)·2026
Same author

Guidance in the application of quality management in the field of chromatography in routine medical laboratories - EFLM Committee: Accreditation and ISO/CEN Standards point of view.

Clinical chemistry and laboratory medicine·2026
Same author

Biological Variation of Natriuretic Peptides and Other Cardiovascular Disease-Related Biomarkers: A Systematic Review and Meta-analysis.

Clinical chemistry·2026
Same author

Awareness, attitudes, and perceived barriers to artificial intelligence adoption in Turkish clinical biochemistry laboratories: An exploratory cross-sectional survey.

Annals of clinical biochemistry·2026
Same author

Impact of sample size and data origin on the simulation-based analytical performance specification derivation.

Clinical chemistry and laboratory medicine·2026

相关实验视频

Updated: Jul 9, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.3K

基于机器学习的临床决策支持,使用实验室数据.

Hikmet Can Çubukçu1,2, Deniz İlhan Topcu3, Sedef Yenice4

  • 1General Directorate of Health Services, Rare Diseases Department, Turkish Ministry of Health, Ankara, Türkiye.

Clinical chemistry and laboratory medicine
|November 28, 2023
PubMed
概括

人工智能 (AI) 和机器学习 (ML) 通过改善患者结果和工作流程效率来增强实验室医学. 挑战包括模型不确定性和数据采集,但人工智能驱动的临床决策支持系统显示出很大的前景.

关键词:
临床实验室临床实验室数据数据的数据数据的数据.决策支持提供了决策支持.机器学习是机器学习.总体测试过程的测试过程.

更多相关视频

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.5K
Author Spotlight: Developing a Point-of-Care Hemoglobin Estimation Method for Anemia Management
05:35

Author Spotlight: Developing a Point-of-Care Hemoglobin Estimation Method for Anemia Management

Published on: January 19, 2024

835

相关实验视频

Last Updated: Jul 9, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.3K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.5K
Author Spotlight: Developing a Point-of-Care Hemoglobin Estimation Method for Anemia Management
05:35

Author Spotlight: Developing a Point-of-Care Hemoglobin Estimation Method for Anemia Management

Published on: January 19, 2024

835

科学领域:

  • 实验室医学 实验室医学
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 人工智能 (AI) 和机器学习 (ML) 越来越多地成为现代医疗保健的组成部分.
  • 这些技术正在改变临床实验室的工作流程和患者护理.

研究的目的:

  • 审查ML模型在实验室医学中的发展.
  • 检查它们对临床实验室工作流程和患者结果的影响.
  • 讨论ML整合的挑战和未来方向.

主要方法:

  • 总结了ML模型的开发过程,包括数据收集,清理,功能工程和优化.
  • 审查了ML在临床决策支持系统 (CDSS) 中的应用,以解释测试结果.
  • 讨论了ML在分析前,分析后和分析后实验室阶段的整合.

主要成果:

  • 机器学习模型,包括来自自动机器学习工具的机器学习模型,简化了实验室流程并提高了效率.
  • 使用ML的CDSS帮助医疗保健专业人员解释测试结果,增强决策能力.
  • 尽管面临挑战,在所有实验室阶段进行ML集成提供了显著的潜力.

结论:

  • 基于ML的CDSS可以大大改善医疗保健中的临床决策.
  • 成功采用需要解决模型不确定性,黑子问题和数据采集挑战.
  • 协作,混合智能和严格的验证对于有效实施至关重要.