Integrating deep learning, social networks, and big data for healthcare system

Abstract This paper aims to propose a deep learning model based on big data for the healthcare system to predict social network data. Social network users post large amounts of healthcare information on a daily basis and at the same time hospitals and medical laboratories store very large amounts of healthcare data, such as X-rays. The authors provide an architecture that can integrate deep learning, social networks, and big data. Deep learning is one of the most challenging areas of research and is becoming increasingly popular in the health sector. It uses deep analysis to extract knowledge with optimum precision. The proposed architecture consists of three layers: the deep learning layer, the big data layer, and the social networks layer. The big data layer includes data for health care, such as X-ray images. For the deep learning layer, three Convolution Neuronal Network models are proposed for X-ray image classification. As a result, social network layer users can access the proposed system to predict their X-ray image posts.

• deep learning
• social networks
• big data
• health care system
• X-ray image classification
• convolutional neural networks
• social media health data

• 3 — الصحة الجيدة والرفاه

• Artificial Intelligence in Healthcare
• Artificial Intelligence in Healthcare and Education
• Internet of Things and AI
• deep learning
• social networks
• big data
• health care system
• X-ray image classification
• convolutional neural networks
• social media health data
• Health Information Management
• Health Informatics
• Information Systems
• Health Professions
• Medicine
• Computer Science