Innovating Healthcare: Renewable Energy Amplifies Diagnostic Imaging Analysis through RPA and Deep Learning


Article type :

1

Author :

1Eugene Bradley, 2Mason Roy 1,2Department of Engineering, Louisiana State University, USA Email: masonjeffir@gmail.com

Volume :

3

Issue :

1

Abstract :

Abstract This paper explores the innovative integration of renewable energy with Robotic Process Automation (RPA) and Deep Learning technologies to amplify diagnostic imaging analysis in healthcare. Renewable energy sources, such as solar and wind power, offer sustainable alternatives to traditional energy grids, reducing carbon emissions and operational costs. By harnessing renewable energy, coupled with the automation capabilities of RPA and the analytical power of Deep Learning, healthcare facilities can drive efficiency and accuracy in diagnostic imaging workflows. This paper investigates the synergistic effects of renewable energy integration, RPA automation, and Deep Learning-based analysis, highlighting their benefits in terms of sustainability, workflow optimization, and enhanced patient care outcomes.

Keyword :

Keywords: Renewable energy, healthcare innovation, diagnostic imaging analysis, Robotic Process Automation (RPA), Deep Learning, sustainability, workflow optimization, energy efficiency, patient care