A Machine Learning-Based Non-Invasive System for Blood Group Prediction Using Fingerprint Biometrics

Year : 2025 | Volume : 12 | Issue : 03 | Page : 9 18
    By

    Ritika Yadav,

  • Saubhagya,

  1. Student, Department of CSE ABES Institute of Technology Ghaziabad, Uttar Pradesh, India
  2. Student, Department of CSE ABES Institute of Technology Ghaziabad, Uttar Pradesh, India

Abstract

The research is targeted at the creation of innovative solution “Fingerprint Based Blood Group Prediction” for instant, non-invasive blood group determination from analysis of finger impressions, a breakthrough possibility in emergency health care. Sophisticated machine learning can be employed to map fingerprint patterns to corresponding blood group information and overcome the current lack of a direct connection between the two. Integration of various technologies: employed React for frontend development, Flask for backend, MySQL for database management, and the utilization of Python with TensorFlow/OpenCV for the machine learning model. The fingerprint scanner reads fingerprint data, which is preprocessed and analysed using a Convolutional Neural Network (CNN) to make predictions about blood groups. The most important implementation stages involve the setup of the development environment, capturing and preprocessing fingerprint data, integration of ML model training, backend API construction and frontend UI design. RESTful APIs will help the system and application interact seamlessly on cloud platforms. The success of this project may have the potential to revolutionize blood group typing in emergency situations through provision of a rapid and non-invasive method

Keywords: Blood Group Prediction, Fingerprint Analysis, CNN, Deep Learning, Biometrics

[This article belongs to Research & Reviews: A Journal of Bioinformatics ]

How to cite this article:
Ritika Yadav, Saubhagya. A Machine Learning-Based Non-Invasive System for Blood Group Prediction Using Fingerprint Biometrics. Research & Reviews: A Journal of Bioinformatics. 2025; 12(03):9-18.
How to cite this URL:
Ritika Yadav, Saubhagya. A Machine Learning-Based Non-Invasive System for Blood Group Prediction Using Fingerprint Biometrics. Research & Reviews: A Journal of Bioinformatics. 2025; 12(03):9-18. Available from: https://journals.stmjournals.com/rrjobi/article=2025/view=230981


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Regular Issue Subscription Review Article
Volume 12
Issue 03
Received 23/08/2025
Accepted 01/09/2025
Published 11/11/2025
Publication Time 80 Days
186

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