Safeguarding Patient Safety and Care Quality through Computer Vision and AI: Creating Smart Systems for Medication Management, Fall Detection, and Infection Control in Healthcare Settings

Abstract

Patient safety and quality of care are paramount concerns in healthcare facilities, and technology plays an increasingly important role in addressing these challenges. Computer vision and artificial intelligence (AI) have emerged as promising tools for enhancing patient safety and improving the quality of care in various healthcare settings. This research article explores the development of intelligent systems leveraging computer vision and AI techniques for medication administration, fall detection, and infection control in healthcare facilities. By examining the current state of research, case studies, and future prospects, we aim to highlight the potential of these technologies in reducing medical errors, preventing patient harm, and optimizing care delivery processes. The article also discusses the challenges and considerations associated with the implementation of AI-driven patient safety systems, including data privacy, system reliability, and the need for human oversight and collaboration.