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Original Article

Gynaecological Disease Diagnosis Expert System (Gyneexpert)

Open Access Peer Reviewed Crossref DOI

Authors

  • Dr R Balakrishna1
  • Sneha B S2
  • Soumya3
  • Vidya J L4
  • Varsha S V5

1 Principal, Department of Computer Science and Engineering RajaRajeswari College of Engineering Bengaluru, Karnataka, India. 2 3 4 5 Department of Computer Science and Engineering RajaRajeswari College of Engineering Bengaluru, Karnataka, India.

Article Information

Published Online
September-December 2025
Pages
363-368
Article Type
Original Article
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Abstract

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GyneExpert is an intelligent web-based application designed to offer early guidance for gynaecological health concerns by combining deep learning with natural language processing techniques. The system uses a multi-layer Artificial Neural Network (ANN), trained on clinical dialogue data, to understand symptoms described by users and deliver meaningful, context-aware responses. To process user input effectively, the text is cleaned and transformed using the Lancaster Stemmer and a bag-of-words model, allowing the system to capture important linguistic features. To improve the accuracy of its predictions, GyneExpert incorporates an intent recognition mechanism supported by probabilistic thresholding, ensuring that responses are both relevant and reliable. The platform is built using the Flask framework and integrates a SQLite database for secure user authentication and organised storage of chat histories. In addition to its technical capabilities, the application offers a clean and responsive interface with text-to-speech support, making it more accessible for a wide range of users. It also connects users to trustworthy medical resources, helping them make safer and more informed health decisions. Overall, GyneExpert aims to provide a supportive digital companion for individuals seeking early insights into their gynaecological health.

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