Deep Learning in Healthcare System for Quality of Service.

Journal: Journal of healthcare engineering
Published Date:

Abstract

Deep learning (DL) and machine learning (ML) have a pivotal role in logistic supply chain management and smart manufacturing with proven records. The ability to handle large complex data with minimal human intervention made DL and ML a success in the healthcare systems. In the present healthcare system, the implementation of ML and DL is extensive to achieve a higher quality of service and quality of health to patients, doctors, and healthcare professionals. ML and DL were found to be effective in disease diagnosis, acute disease detection, image analysis, drug discovery, drug delivery, and smart health monitoring. This work presents a state-of-the-art review on the recent advancements in ML and DL and their implementation in the healthcare systems for achieving multi-objective goals. A total of 10 papers have been thoroughly reviewed that presented novel works of ML and DL integration in the healthcare system for achieving various targets. This will help to create reference data that can be useful for future implementation of ML and DL in other sectors of healthcare system.

Authors

  • Dibyahash Bordoloi
    Department of Computer Science and Engineering, Graphic Era University, Dehradun, Uttarakhand, India.
  • Vijay Singh
    Department of Computer Science and Engineering, Graphic Era University, Dehradun, Uttarakhand, India.
  • Sumaya Sanober
    Prince Sattam Bin Abdul Aziz University, Wadi Al Dawasir 1191, Saudi Arabia.
  • Seyed Mohamed Buhari
    Department of Information Technology, King Abdulaziz University, PO Box 80221, Jeddah 21589, Saudi Arabia.
  • Javed Ahmed Ujjan
    Department of Zoology, Shah Abdul Latif University Khairpur, Khairpur, Sindh, Pakistan.
  • Rajasekhar Boddu
    Department of Software Engineering, College of Computing and Informatics, Haramaya University, Dire Dawa, Ethiopia.