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Alleviate: An AI-Powered Mobile Application for Personalized Healthcare Management and Doctor Recommendation

  • A. N. Saritha
  • , Gauri Kalnoor*
  • , Pannaga R. Bhat
  • , Pranav Anantha Rao
  • , P. Prajwal
  • , P. T. Pradeep
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The areas of access and control in the healthcare industry are probably one of the most significant areas that could greatly benefit from advancements in technology. The mobile application developed in this paper is based on the latest research techniques aimed at providing comprehensive health care services to its users, including patients and healthcare providers. This application was built using Flutter and Dart for the frontend and Flask for the backend along with Firebase for data storage. It uses machine learning techniques like Logistic Regression (LR) and Random Forest (RF) to create predictive models for specialists, dietary habits and physical exercise using carefully curated datasets, enriched by the implementation of Natural Language Processing (NLP) techniques achieving 97.24% precision using Logistic Regression Model (LR). In addition to this, it also supports doctor authentication through secure web automation since it authenticates physicians through the Indian Medical Registry (IMR). The application has many functional features such as scheduling appointments, managing prescriptions, and using a clinic dashboard, which make it more useful for healthcare professionals. It also provides personalized diet and exercise plans based on the individual health metrics as well as location-based features, using OpenStreetMap and geospatial analysis to help navigate to the nearest healthcare services. It also facilitates a report generation system with artificial intelligence that equips health care professionals with an overall history of a patient’s medical past, thus supporting both diagnosis and treatment plans. The range of features in this application like the ones listed above makes the solution one of a kind. The innovative aspects of the application like voice recognition technology and QR code scanning introduce various key enhancements in terms of current systems. This comprehensive healthcare solution utilizes advanced technology to bridge gaps in healthcare services, offering a secure and user-friendly platform for patients and healthcare professionals alike.

Original languageEnglish
Pages (from-to)215822-215832
Number of pages11
JournalIEEE Access
Volume13
DOIs
Publication statusPublished - 2025

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Materials Science
  • General Engineering

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