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相关概念视频

Rh Blood Group01:19

Rh Blood Group

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The Rhesus (Rh) antigen is crucial in determining blood groups and ensuring compatibility during blood transfusions.
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Blood Typing01:10

Blood Typing

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Understanding an individual's blood group is a critical component of transfusion medicine. It ensures compatibility in blood transfusions, organ transplants, and even during pregnancy. Determining these blood groups involves the ABO and Rh blood typing systems, utilizing specific antigens and corresponding anti-sera to identify an individual's blood type.
Antigens are protein molecules that reside on the surface of red blood cells (RBCs). The ABO and Rh blood typing systems target...
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Blood Types02:20

Blood Types

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Human blood is classified into different types based on the presence of antigens on the red blood cell's surface and antibodies in the plasma. Proper identification of blood type is essential for successful blood transfusion. The International Society of Blood Transfusion has identified 38 human blood types based on the surface antigens on the red blood cells. The most common types are ABO, Rh, and MNS blood types.
ABO blood group
ABO antigens are glycoproteins encoded by genes present on...
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Blood Transfusion and Agglutination02:45

Blood Transfusion and Agglutination

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Blood transfusion is a therapeutic measure to restore the blood volume after extensive blood loss due to an accident or a medical procedure. Blood transfusion involves drawing a certain amount of blood from a suitable donor and infusing it into the recipient.
History
The history of blood transfusion dates back to the 17th century, when early attempts were made in animals. In 1818 James Blundell, a British doctor, performed the first successful human blood transfusion. Later in 1900, Karl...
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Prediction of Red Blood Cell Antibody Significance Using the Monocyte-Macrophage Assay
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Prediction of Red Blood Cell Antibody Significance Using the Monocyte-Macrophage Assay

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RhDnostics:一种基于机器学习的预测算法模型,用于 RhD 阴性和 DEL 血型查.

Meechoke Choodoung1, Charuporn Promwong2, Ketsaraporn Wongba2

  • 1Department of Mathematics, Faculty of Science, Mahidol University, Bangkok, Thailand.

The journal of applied laboratory medicine
|May 30, 2025
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概括

一个机器学习算法准确地识别了RhD阴性血型,有助于选D-elution (DEL) 红细胞. 这种工具可以改善实验室实践和患者安全,在无法进行确认性测试的情况下.

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科学领域:

  • 免疫学 免疫学 免疫学
  • 遗传学 遗传学 是一个
  • 计算生物学 计算生物学

背景情况:

  • 由于红细胞上的低D抗原表达,D-elution (DEL) 现型经常被误认为Rh阴性.
  • 标准的确认方法,如吸附脱离试验和基因定型,在实验室实践中面临挑战,影响患者的安全.
  • 这些挑战包括长时间的交付时间,仪器和试剂的可用性,预算限制和技术困难.

研究的目的:

  • 开发一种用于查D-elution (DEL) 和RhD阴性血型的预测算法.
  • 利用机器学习来准确识别这些血型.

主要方法:

  • 使用 RhCcEe 抗原测试的血清学数据开发了一个机器学习模型.
  • 该模型包含了用于DEL确认的吸附-化试验数据.
  • 该算法是在泰国献血者数据集上进行训练和验证的.

主要成果:

  • 机器学习算法在 RhD 阴性识别方面实现了超过 90% 的预测准确度.
  • 该算法证明了与或没有DEL确认血清学测试的有效性.
  • 一个名为 RhDnostics 的网络应用程序被开发出来,以促进 RhD 阴性查.

结论:

  • 开发的机器学习算法作为实验室RhD阴性查的有价值的预测工具.
  • 当确认血清学测试或RHD分子测试无法获得时,它提供了一个可行的解决方案.
  • 这种方法提高了血液储存中的实验室效率和患者安全.