Year: 2025
Type: article
Abstract: The demand for AI-driven intelligent healthcare systems has increased due to the rising need for prompt and effective healthcare solutions, particularly since 5G connection makes it possible to gather and process data from medical devices in real time. Accurate and timely identification of serious illnesses including heart disease, renal failure, liver problems, malaria, and pneumonia is frequently a challenge for traditional healthcare. In order to solve this, our project suggests an AI-powered healthcare system that uses 5Gcapable devices to gather data in realtime. It uses sophisticated machine learning and deep neural networks to identify a variety of illnesses and offer preventative measures and treatments. In addition to CNN algorithms for malaria with 96.01% efficiency including pneumonia with 98.16% accuracy, the system uses Random Forest Classifier for cardiovascular disease with a precision of 99%, renal disease with 98.3% reliability, and liver cancer with 98.64% efficiency utilizing SMOTE for class imbalance. A Flask-based user interface (UI) enables immediate monitoring and interaction, while preprocessing methods like exploratory data analysis (EDA) guarantee data quality, providing a thorough and adaptable healthcare solution.
Authors: D.Sarika, D. Sukanya, G. Srujanasri Reddy, M. Teja, M. TharunSai
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4409959144