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

Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy01:26

Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy

353
This lesson explores three gastrointestinal imaging techniques: radionuclide testing, colonic transit studies, and virtual colonoscopy.
Radionuclide Testing
Radionuclide testing is a sophisticated medical technique for assessing gastrointestinal motility. It focuses on gastric emptying and colonic transit time. Radioactive markers track the movement of food through the digestive system, providing insights into gastrointestinal disorders.
In gastric emptying studies, a meal's liquid and...
353
Classification of Illness01:17

Classification of Illness

8.5K
The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
8.5K
Endoscopic Procedures II: Colonoscopy01:25

Endoscopic Procedures II: Colonoscopy

568
The colon, or large intestine, is the final segment of the digestive system. Its primary functions include absorbing water and vitamins produced by gut bacteria and transforming waste from liquid to solid to form stool. In adults, the large intestine is approximately 5 feet long and consists of four main sections:
568

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

Identification of Patients for a Community Health Worker Program Using an Artificial Intelligence Algorithm.

Learning health systems·2026
Same author

Multimodal AI for early prediction of adverse clinical outcomes in acute pancreatitis.

Abdominal radiology (New York)·2026
Same author

Increasing colorectal cancer screening among Alaska Native peoples living in remote areas of Alaska: a multitarget stool DNA cluster randomized controlled trial.

BMC primary care·2026
Same author

A lifecycle governance and learning health system framework for trustworthy, generalizable, and sustainable human-ai partnership in clinical practice: Lessons from the asthma-guidance and prediction system (A-GPS).

Journal of the National Medical Association·2026
Same author

Kallikrein related peptidases 7 and 10 and their substrate desmoglein 3 are upregulated in early stage pancreatic cancerous lesions.

Scientific reports·2026
Same author

Correction to: Multi-center evaluation of radiomics and deep learning to stratify malignancy risk of IPMNs.

Abdominal radiology (New York)·2026

相关实验视频

Updated: Jan 9, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

472

使用机器学习和自然语言处理精确和可扩展的分类结肠镜新生病.

Brendan Broderick1, Jason Greenwood2, Douglas Mahoney3

  • 1Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.

Clinical and translational gastroenterology
|December 9, 2025
PubMed
概括

一个机器学习模型从电子健康记录中准确地分类结直肠瘤,改善结直肠镜质量监测. 这种自然语言处理系统增强了腺瘤和状病变的检测.

更多相关视频

Structured Approach to Colonoscopy Technique Optimization: A Single-Center Experience with Novice Endoscopists
03:43

Structured Approach to Colonoscopy Technique Optimization: A Single-Center Experience with Novice Endoscopists

Published on: July 11, 2025

579
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

8.6K

相关实验视频

Last Updated: Jan 9, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

472
Structured Approach to Colonoscopy Technique Optimization: A Single-Center Experience with Novice Endoscopists
03:43

Structured Approach to Colonoscopy Technique Optimization: A Single-Center Experience with Novice Endoscopists

Published on: July 11, 2025

579
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

8.6K

科学领域:

  • 医疗信息学医学信息学
  • 机器学习在医疗保健中的应用
  • 胃肠道学和瘤学

背景情况:

  • 结肠直肠癌 (CRC) 是美国癌症死亡的主要原因.
  • 结肠镜是预防CRC的主要查方法.
  • 从内镜和病理学来准确识别结直肠瘤对于质量评估至关重要.

研究的目的:

  • 评估随机森林机器学习模型用于分类结直肠瘤的可行性.
  • 开发一种自然语言处理 (NLP) 系统来对电子健康记录中的发现进行分类.

主要方法:

  • 在一个大型学术机构进行了一项回顾性队列研究.
  • 开发了一个基于规则的算法,以从内镜和病理学数据中对瘤进行分类.
  • 一个随机的森林NLP系统被训练在非结构化的病理发现和验证在一个独立的集.

主要成果:

  • 该模型接受了35953份病理学报告和95188份结肠镜报告的训练.
  • 在一个独立的验证集上,NLP系统实现了高精度.
  • 曲线下的面积 (AUC) 值为腺瘤的0.997,状的0.99和晚期病变的0.99.

结论:

  • 一个基于森林的随机NLP系统准确且可解释地对结肠镜检查结果进行分类.
  • 与机器学习相结合的NLP为结肠镜质量监测提供了一个可扩展的策略.
  • 这种方法可以提高瘤检测的准确性和患者的治疗结果.