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相关概念视频

Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...

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相关实验视频

Updated: Jun 20, 2026

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
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基于任务驱动的框架,使用数字病理学的大型模型.

Jiahui Yu1,2, Tianyu Ma2, Feng Chen3

  • 1Department of Biomedical Engineering, MOE Key Laboratory of Biomedical Engineering, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, China.

Communications biology
|December 5, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了自动化显微镜的大型模型驱动框架,增强了数字病理学. 它使组织幻灯片的智能实时分析成为可能,减少了诊断中的手工劳动.

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Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment
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Multiparametric Tumor Organoid Drug Screening Using Widefield Live-Cell Imaging for Bulk and Single-Organoid Analysis
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科学领域:

  • 数字病理学数字病理学
  • 生物医学成像技术 生物医学成像技术
  • 人工智能的人工智能

背景情况:

  • 使用显微镜进行病理诊断的手动注释,测量和解释是耗时和昂贵的.
  • 目前的显微镜方法对大规模生物医学数据分析的效率和可扩展性存在局限性.

研究的目的:

  • 开发一个新的任务驱动的框架,利用大型模型进行先进的显微镜应用.
  • 展示AI驱动显微镜在自动化和增强病理诊断方面的潜力.

主要方法:

  • 实施一个以任务为导向的框架,由具有视觉分析和实时控制专业知识的大型模型驱动.
  • 在临床任务上应用和概念验证,特别是对H&E染色肝脏组织幻灯片的自适应分析.

主要成果:

  • 在临床任务中成功展示了概念验证,涉及H&E染色肝脏组织幻灯片.
  • 该框架显示了适应性分析的先进功能,表明临床实用性的巨大潜力.

结论:

  • 拟议的框架代表了迈向下一代智能显微镜的重大进展.
  • 这项工作为数字病理学和临床应用中的高效,实时和智能分析制定了新的标准.