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Beyond Blood Tests: Using Deep Learning to Identify Blood Groups Through Fingerprint Analysis

D. Rohini, A. Pooja, Sindhu ., Syeda Hifsa Naaz

Abstract


Particularly in an emergency where fast identification is needed, medical diagnostics depend on exact and non-invasive blood group detection. Conventional blood type techniques involving serological analysis ask for direct blood samples and might be time-consuming. Aside from creating new opportunities for quick, contactless blood group identification, this work advances biometric-based medical diagnostics. Because of their tenacity and individuality, fingerprints possessing their distinct ridge patterns have always been utilized in biometric identification. By offering a rapid, reasonably priced, and safe replacement for traditional blood group detection, this method opens the path for advancements in biometric-driven medical diagnostics. In this research, we propose a harmless deep learning based technique using fingerprint photos for blood group classification that aims to extract and assess fingerprint patterns utilizing biometric correlations with blood group characteristics.


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References


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