Supervised and Unsupervised Data Engineering for Multimedia Data

3Multimedia Data in Healthcare System

Sarita Gulia¹, Pallavi Pandey² and Yogita Yashveer Raghav^3*

¹Department of Computer Science and Engineering, K. R. Mangalam University, Gurugram, Haryana, India

²School of Engineering & Technology, K. R. Mangalam University, Gurugram Haryana, India

³Computer Science Department at K. R. Mangalam University, Gurugram, Haryana, India

Abstract

Data that combines many media is multimedia. Types of data include text, numbers, images, audio, and video. Multimedia is crucial for presenting information. It has diverse applications in education, training, business, advertising, and entertainment. Multimedia data can feed neural network models for disease diagnosis and prediction, benefiting the healthcare business. Feature identification, extraction, and analysis can use several machine learning methods. Multimedia technology allows subjects to view diagnosis images such as X-rays, CT scans, and MRI scans to grasp the issue better. Detection and staging of illness are possible. Combining multimedia techniques and technology can improve doctor-patient communication. With multimedia technology, patients may easily recall offered information, promoting therapeutic progress. New algorithms in a cloud system can improve multimedia data management, including patient, specialized doctor, and nursing details. Multimedia components include text, images, sounds, videos, and graphics. Video representation of data improves understanding of diseases and therapy, ...