Multimedia Data in Healthcare System
Sarita Gulia, Pallavi Pandey, Yogita Yashveer Raghav · 2024
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, according to the survey. Using multimedia technology in diagnostic methods such as CT scans, X-rays, and MRI has enhanced patients’ quality of life. It also enhances the quality of life for those with disabilities. Digital media data can be quickly adjusted and comprehended by patients, improving therapy satisfaction. The surgical process can be enhanced with multimedia tools and methods. This chapter covers multimedia tools and strategies for smart healthcare systems. Interactive multimedia tools and machine learning will be introduced to healthcare. Critical applications include Multimedia data visualization, Computer vision for healthcare monitoring, and Machine learning for brain dysfunction, and cancer detection. This article will cover machine learning methods for disease diagnosis and prediction using diagnostic tools. The use of multimedia tools can improve patient care compared to traditional methods. Deep learning algorithms can be utilized for image and video analysis. This chapter will also address the security of multimedia data in healthcare. We will also focus on neural networks for diagnosing multimedia-based data.