Utilização da inteligência artificial no aprimoramento da predição de manutenção em equipamentos médicos-hospitalares

Abstract

The Artificial Intelligence in Healthcare has undergone a remarkable evolution in the last three decades, driven by the emergence of Machine Learning (ML) and Deep Learning (DL). This progression has led to extensive applications, facilitating a shift from medicine solely based on algorithms to a personalized medicine approach. Artificial Intelligence (AI) stands out as a transformative tool, enhancing diagnostic accuracy, optimizing efficiencies in healthcare professionals' workflows and clinical operations, facilitating disease and treatment monitoring, and refining procedure accuracy, thereby positively impacting outcomes for patients. This study focuses on the comprehensive evaluation of the application of Artificial Intelligence in predicting the maintenance of medical-hospital equipment. The primary objective is to analyze potential improvements in processes, the associated cost impacts, and the contribution to efficient Clinical Engineering management. Additionally, it addresses the challenges faced and future prospects in this ever-evolving scenario. By exploring the implementation of Artificial Intelligence in this specific context, the study aims to provide insights to optimize the operation of medical equipment, considering aspects such as fault prediction, predictive maintenance, and proactive asset management. This predictive approach not only enhances the quality of healthcare but also positively impacts resource management, promoting a more proactive and effective approach to maintaining and enhancing medical infrastructure. However, the future of AI in healthcare also brings uncertainties regarding its comprehensive impact on human life. The research emphasizes the need to anticipate developments in progress and proactively address ethical and practical issues that may arise in this dynamic and transformative landscape.