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Related Concept Videos

Blood Typing01:10

Blood Typing

1.2K
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...
1.2K
Blood Types02:20

Blood Types

17.6K
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 Transfusion01:15

Blood Transfusion

552
Blood transfusion is a critical medical procedure that saves lives and treats various medical conditions. It involves transferring blood from a donor to a recipient. This process requires a thorough understanding of the ABO blood group system and its associated antigens and antibodies.
Blood Transfusion Overview
A blood transfusion is a medical procedure used to replace blood lost due to injury, surgery, or to treat conditions such as anemia or cancer. During a transfusion, donor blood is...
552
Blood Transfusion and Agglutination02:45

Blood Transfusion and Agglutination

10.8K
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...
10.8K

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Related Experiment Video

Updated: Jun 29, 2025

A Precision Medicine Tool for Measurement and Monitoring of Hemoglobin S in Sickle Cell Disease Patients Receiving Transfusion Therapy
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Image-based second opinion for blood typing.

Sergey Korchagin1,2, Ekaterina Zaychenkova1,2, Egor Ershov1,2

  • 1Institute for Information Transmission Problems, Moscow, Russia.

Health Information Science and Systems
|April 5, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new AI method to improve manual blood typing accuracy. The neural network achieves 98.4% accuracy, significantly reducing errors compared to human analysis in blood typing.

Keywords:
AgglutinationBlood typingClassificationDeep learningImage analysisNeural networks

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Area of Science:

  • Medical Diagnostics
  • Artificial Intelligence in Healthcare
  • Clinical Laboratory Science

Background:

  • Manual blood typing using serological plates is a common but error-prone diagnostic method.
  • The process involves visual agglutination assessment, which is susceptible to human error and time-consuming.
  • Improving the accuracy and efficiency of blood typing is crucial for patient safety and healthcare systems.

Purpose of the Study:

  • To develop and evaluate a novel neural-based classification method for automated blood typing analysis.
  • To enhance the quality and performance of the agglutination analysis step in manual blood typing.
  • To provide a reliable second opinion for laboratory assistants in blood typing procedures.

Main Methods:

  • A new dataset of 3139 well images with ground truths and expert assessments was collected.
  • State-of-the-art neural network architectures were employed for image classification.
  • Shallow neural networks were also investigated due to the task's low-semantic nature.

Main Results:

  • The proposed neural-based method achieved an overall accuracy of 98.4%.
  • The AI solution demonstrated 2.75 times fewer errors than the average human expert.
  • Performance was comparable to the best human expert, with shallow networks showing similar accuracy to advanced models.

Conclusions:

  • The neural-based classification method significantly improves the accuracy and reduces errors in manual blood typing.
  • AI offers a viable and efficient solution for the analysis step in blood typing, complementing human expertise.
  • The developed system can be integrated into laboratory systems for faster and more reliable results.