Year: 2025
Type: article
Abstract: Blood grouping plays a crucial role in medical diagnostics, transfusion practices, and forensic investigations. Traditionalmethods for determining blood groups involve serological testing of blood samples, which, while accurate, requireinvasive procedures, trained personnel, and time. Researchers have recently explored non-invasive alternatives, amongwhich biometric approaches such as fingerprint analysis have gained attention. The emerging field of fingerprint-basedblood grouping presents a revolutionary, non-invasive alternative by leveraging the unique biochemical composition offingerprint residues and the distinct patterns of epidermal ridges. This approach offers significant value by enabling rapid,cost-effective, and hygienic blood type determination, with profound benefits for enhancing emergency response efficiency,streamlining donor registration in blood banks, and advancing forensic investigations. The purpose of this comprehensivereview is to synthesize current research and provide a detailed overview of the methodologies underpinning thistechnology. We examine the scientific basis for the correlation between fingerprint patterns and ABO/Rh blood groups,evaluate traditional chemical and spectroscopic techniques, and analyze the cutting-edge integration of artificial intelligence(AI) and deep learning models for automated classification. Furthermore, the review discusses the practical applications,advantages, and current limitations of the technology, concluding with an outlook on future directions for research andimplementation. This paper underscores the transformative potential of fingerprint-based blood grouping as a viable andpromising solution for modern medical and forensic challenges. However, further research with larger and more geneticallydiverse populations is required to validate and refine the predictive models. In conclusion, while fingerprint-based bloodgrouping cannot yet replace conventional methods, it offers a compelling supplementary tool for rapid, non-invasive bloodgroup estimation.
Source: Medico-Legal Update
DOI: 10.37506/65z8av60
Authors: Sanskriti Rani Sharma, Sanskriti Rani Sharma, Dinesh Sharma, Vijay Panchal, Palack Asati, Palack Asati
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W7083021951
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