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相关概念视频

Inflammatory Bowel Disease V: Surgical Management01:21

Inflammatory Bowel Disease V: Surgical Management

164
Surgical interventions for inflammatory bowel disease (IBD), which includes ulcerative colitis and Crohn's disease, are essential in managing symptoms and addressing complications. The selection of surgical procedures is contingent upon the specific conditions and complications that stem from these illnesses.
Here are some common surgical interventions for IBD:
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Ostomy Care01:24

Ostomy Care

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Introduction
An ostomy is a surgical procedure that creates an artificial opening from the intestines to the outside of the body, allowing for the rerouting of effluent. This opening is known as a stoma. A stoma usually protrudes above the skin surface, appearing pink or red, moist, and round, and it lacks nerve sensations.
There are different types of ostomies, including colostomies, ileostomies, and urostomies:
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Endoscopic Procedures IV: Sigmoidoscopy and Laproscopy01:26

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Sigmoidoscopy and laparoscopy are distinct medical procedures that enable physicians to internally inspect different parts of the GI tract. Although they serve different purposes, each is essential for diagnosing and, in some cases, treating various medical conditions.
Sigmoidoscopy
Sigmoidoscopy is a diagnostic procedure that uses a flexible sigmoidoscope equipped with a light source and camera to examine the rectum and sigmoid colon. The procedure involves inserting the tube through the anus...
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Application of End-to-end Anastomosis in Robotic Central Pancreatectomy
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基于人工智能的系统,用于预测关节节省操作后的永久性静脉阻塞.

Chih-Yu Kuo1, Li-Jen Kuo2,3,4, Yen-Kuang Lin5

  • 1Department of Surgery, Taipei Medical University Hospital, Taipei, Taiwan.

Scientific reports
|September 25, 2023
PubMed
概括

人工智能模型可以准确地预测直肠癌手术后发展永久性静脉口腔的可能性. 这种人工智能工具利用手术前的数据来预测门的结果,帮助知情同意和治疗规划.

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科学领域:

  • 在瘤学瘤学.
  • 手术瘤学手术瘤学
  • 医疗人工智能 医疗人工智能

背景情况:

  • 对于直肠癌而言,节节约手术的目的是保持胃肠连续性.
  • 一部分患者在手术后出现永久性静脉栓塞 (PS),尽管确定了危险因素.
  • 准确的手术前预测PS形成仍然是一个临床挑战.

研究的目的:

  • 验证一种人工智能 (AI) 模型,用于预测永久性静脉口腔 (PS) 的形成.
  • 评估人工智能模型的准确性,使用常规可用的术前变量,用于接受关节节省手术的直肠癌患者.

主要方法:

  • 428名接受了关节节约手术 (2012-2021) 的直肠癌患者的回顾性分析.
  • 机器学习算法 (包括随机森林,XGBoost,LightGBM) 在19个手术前变量上受过训练.
  • 模型性能使用准确度,灵敏度,特异性和AUC进行评估,数据分为训练 (80%) 和验证 (20%) 集.

主要成果:

  • 总体永久性静脉口腔 (PS) 率为13.6%.
  • 随机森林和轻GBM模型显示出最高的预测准确性 (分别为95%和93%) 和AUC (0.99和0.98).
  • 确定的主要预测因素包括门边缘的损伤距离,临床N阶段,年龄,性别,ASA得分和手术前的白蛋白/CEA水平.

结论:

  • 人工智能模型与手术前数据相结合,可以有效地预测关节节省直肠癌手术后的口腔结局.
  • 开发的AI模型显示出出色的预测能力,有可能增强患者的知情同意过程.
  • 这种方法为改善患者咨询和在直肠癌管理中的手术规划提供了有价值的工具.