Blood Group Detection Using Fingerprint

In forensic investigations, emergency medical care, and medical diagnostics, blood group identification is essential. Conventional blood group testing techniques necessitate specific equipment and laboratory conditions, as well as invasive procedures. Biometric information, like fingerprints, has become a new and non-invasive method for predicting genetic and physiological traits in recent years. By investigating the relationship between dermatoglyphic patterns and ABO/Rh blood groups, this studyinvestigates the possibility of using fingerprint analysis to determine an individual's blood group. Machine learning algorithms were trained to recognize patterns and predict blood types with promising accuracy using a dataset that included validated blood group data and fingerprint photos. The findings show a statistically significant correlation between particular blood groups and fingerprint ridge patterns, indicating the potential of this method as an additional or initial screening tool. In order to lessen reliance on blood samples for basic health profile, this research suggests a novel approach to biometric-drivendiagnostics.