FemCareAI

Project Code :TCMAAN1184

Objective

To develop a mobile-based expert system for diagnosing gynaecological diseases using Machine Learning and Natural Language Processing, offering personalized AI-driven diagnosis, voice interaction, symptom checking, and prescription generation for empowering users with private, accessible, and informed health insights

Abstract

Pocket Doc is an AI-integrated mobile health application designed to facilitate accessible and intuitive gynaecological disease diagnosis. Utilizing advanced Machine Learning algorithms and Natural Language Processing, the app allows users to register, log in, and interact through a smart chatbot powered by Gemini AI. Features include a comprehensive symptom checker, AI-driven diagnostic assistance, and the generation of context-based prescriptions with an option to print. Voice command functionality enhances user interaction, allowing seamless access to health-related information. The system aims to bridge the gap in timely diagnosis and self-awareness of gynaecological issues, particularly for users in areas with limited healthcare access. By enabling conversational engagement, Pocket Doc empowers individuals with knowledge, early warnings, and possible solutions for managing their health. It ensures privacy, efficiency, and personalized support without the need for physical consultations. This application revolutionizes how gynaecological care is approached, making early detection and awareness more achievable and efficient.


Keywords: Gynaecological Health, Machine Learning. NLP, Symptom Checker, Voice Interaction, Digital Prescription.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

Hardware Requirements

  • Processor                       -    I3/Intel Processor
  • RAM                             -    8 GB
  • Hard Disk                      -    1TB

Software Requirements

  • Operating System          -        Windows 10   
  • JDK                                -        java
  • Plugin                             -       Kotlin
  • SDK                                -       Android
  • IDE                                 -       Android studio
  • Database                         -       Room DB

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