Blood Group Detection Using Artificial Intelligence

Blood group detection is an essential part of healthcare, especially in situations like blood transfusions, organ transplants, and medical emergencies. Traditionally, blood groups are identified using laboratory-based methods that require blood samples, chemical reagents, and trained personnel. These methods, while effective, can be time-consuming, invasive, and prone to human error.In recent years, advancements in technology have introduced artificial intelligence (AI) techniques that can detect blood groups through fingerprints, providing a non-invasive, faster, and more accurate alternative. AI-based finger machines analyze patterns and features in fingerprints to predict blood group types without the need for drawing blood.This review paper explores both traditional and AI-based methods for blood group detection. It explains how AI finger machines work, compares them with old methods, discusses their advantages and limitations, and highlights potential applications in hospitals, blood donation camps, and personal healthcare monitoring. The paper also looks at the future prospects of integrating AI blood detection systems with modern healthcare technology to improve efficiency and accessibility.