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

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

Gut microbiota profiles across intrinsic capacity strata in community-dwelling older adults using full-length 16S rRNA sequencing.

GeroScience·2026
Same author

Age-stratified patterns of sarcopenic traits: Evidence for a life-course screening strategy from young adulthood to old age.

Journal of the Formosan Medical Association = Taiwan yi zhi·2026
Same author

A High-Accuracy Rule-Based Algorithm for Automated Extraction of Coronary Artery Calcium Scores from Mixed-Language Radiology Reports.

Journal of imaging informatics in medicine·2026
Same author

Effectiveness of the health literacy education program for medical student clerkships: a one-group pretest-posttest study.

BMC medical education·2026
Same author

Consensus statement on the application of artificial intelligence in osteoporosis screening and management: perspectives from the Asia-Pacific region.

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA·2026
Same author

The impact of patient narrative interview training on medical students' narrative competence - A randomized controlled trial.

Tzu chi medical journal·2026
Same journal

Correction: Luca et al. Global and Regional Diagnostic Results of Progress Toward Cervical Cancer Elimination, According to the WHO Strategy: A Systematic Literature Review with Narrative Synthesis. <i>Diagnostics</i> 2026, <i>16</i>, 1224.

Diagnostics (Basel, Switzerland)·2026
Same journal

Association Between Systemic Inflammatory Response Biomarkers and Disease Activity in Systemic Lupus Erythematosus: A Multi-Center Retrospective Study.

Diagnostics (Basel, Switzerland)·2026
Same journal

Vertebrogenic Low Back Pain and Basivertebral Nerve Ablation: A Review of Mechanisms, Imaging-Driven Selection, and Clinical Outcomes.

Diagnostics (Basel, Switzerland)·2026
Same journal

Multivalvular Carcinoid Heart Disease: The Role of Echocardiography in Diagnosis and Selection for Heterotopic Bicaval Valve Implantation.

Diagnostics (Basel, Switzerland)·2026
Same journal

Data-Efficient and Explainable Multimodal Survival Prediction in NSCLC Using Deep Image Embeddings, Clinical Variables, and Gradient-Boosted Trees.

Diagnostics (Basel, Switzerland)·2026
Same journal

Anomalous Left Coronary Artery from the Pulmonary Artery: Cinematic Volume Rendering Technique for Enhanced Anatomic Visualization.

Diagnostics (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jul 5, 2025

Semiautomated Longitudinal Microcomputed Tomography-based Quantitative Structural Analysis of a Nude Rat Osteoporosis-related Vertebral Fracture Model
07:12

Semiautomated Longitudinal Microcomputed Tomography-based Quantitative Structural Analysis of a Nude Rat Osteoporosis-related Vertebral Fracture Model

Published on: September 28, 2017

8.2K

放射学高级采样技术 免费文本数据 通过深度学习在脊椎骨折中有效构建文本挖掘模型.

Wei-Chieh Hung1,2,3, Yih-Lon Lin4, Chi-Wei Lin1,2

  • 1Department of Family and Community Medicine, E-Da Hospital, I-Shou University, Kaohsiung 82445, Taiwan.

Diagnostics (Basel, Switzerland)
|January 22, 2024
PubMed
概括
此摘要是机器生成的。

先进的采样方法,如向量和最小化,改善了深度学习模型,用于在放射学报告中识别脊椎压缩骨折 (VCF). 这种方法有效地选择关键数据,提高预测准确度.

关键词:
自由文本数据的数据.放射学报告 放射学报告采样方法 采样方法矢量和是一个矢量和.脊椎骨折是指脊椎骨折的发生.

更多相关视频

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.8K
Assessment of Bone Fracture Healing Using Micro-Computed Tomography
12:04

Assessment of Bone Fracture Healing Using Micro-Computed Tomography

Published on: December 9, 2022

1.9K

相关实验视频

Last Updated: Jul 5, 2025

Semiautomated Longitudinal Microcomputed Tomography-based Quantitative Structural Analysis of a Nude Rat Osteoporosis-related Vertebral Fracture Model
07:12

Semiautomated Longitudinal Microcomputed Tomography-based Quantitative Structural Analysis of a Nude Rat Osteoporosis-related Vertebral Fracture Model

Published on: September 28, 2017

8.2K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.8K
Assessment of Bone Fracture Healing Using Micro-Computed Tomography
12:04

Assessment of Bone Fracture Healing Using Micro-Computed Tomography

Published on: December 9, 2022

1.9K

科学领域:

  • 医疗信息学 医疗信息学
  • 自然语言处理自然语言处理.
  • 机器学习 机器学习

背景情况:

  • 在放射学报告中准确识别脊椎压缩骨折 (VCF) 对患者护理至关重要.
  • 传统的文本挖掘方法可能难以应对自由文本临床数据的复杂性和数量.
  • 深度学习模型为语义分析提供了潜力,但需要有效的数据采样策略.

研究的目的:

  • 建立和评估先进的采样方法,以建立高效的语义文本挖掘模型.
  • 用深度学习来比较不同采样技术在从放射学报告中识别VCF时的性能.
  • 为自由文本分析中关键数据选择提出一个优化的抽样方法.

主要方法:

  • 利用了来自脊柱X射线检查的27,401份自由文本放射学报告的数据集.
  • 开发了监督的长期短期记忆 (LSTM) 网络,用于VCF识别.
  • 我们比较了四种采样方法:向量和最小化,向量和最大化,分层和简单随机采样,采用固定百分比 (1/10,1/20,1/30,1/40).
  • 使用接收器操作特征 (AUROC) 曲线下的面积来评估预测准确度.

主要成果:

  • 矢量和最小化始终在所有采样比率中产生最高的AUROC值.
  • 对于向量和最小化的AUROC值在不断下降的采样比率下从0.981到0.895不等.
  • 矢量和最大化证明了最低的预测准确性.
  • 拟议的矢量和最小化方法有效地识别了关键的代表性样本.

结论:

  • 矢量和最小化是一种有效的先进抽样方法,用于构建语义文本挖掘模型的自由文本数据.
  • 这种方法显著提高了深度学习模型的效率和预测准确性,例如LSTM,用于像VCF检测这样的临床应用.
  • 这些发现表明,在医疗自然语言处理任务中优化数据选择的新方法.