ARCHIVES

Original Article

Gynaecological Disease Diagnosis Expert System (Gyneexpert)

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.

Published Online: September-December 2025

Pages: 363-368

Abstract

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.

Related Articles

2025

Transforming Cyber-Physical Systems: Machine Learning for Secure and Efficient Solutions

2025

Exploring AI Techniques for Quantum Threat Detection and Prevention

2025

Maturity Models for Business Intelligence: An Overview

2025

INSPIRO: An AI Driven Institution Auditor

2025

Adaptive AI Framework for Anomaly Detection and DDoS Mitigation in Distributed Systems

2025

Predictive Modeling for College Admission Using Machine Learning and Statistical Methods

Share Article

X
LinkedIn
Facebook
WhatsApp

Or copy link

https://test.indjcst.com/archives/10.59256/indjcst.20250403055

*Instagram doesn't support direct link sharing from web. Copy the link and share it in your Instagram story or post.