ABSTRACT
Artificial intelligence (AI) is a modern approach based on computer research that aims to create algorithms and programs that make machines clever and effective at carrying out jobs that ordinarily require highly educated human intelligence. Deep learning (DL), standard artificial neural, fuzzy logic, and speech recognition are all examples of machine learning (ML), which are only a few of the subsets of AI that have distinctive capabilities and functionalities, making it easier for humans to intervene when it comes to medical assessment, diagnostic devices, and decision-making. The significant difficulties that the healthcare business is confronted with are those that have an influence on the standard of patient treatment. Maintaining data privacy and security is challenging when such a vast amount of sensitive data is present. The patient’s medical record is vulnerable to exposure due to insufficient security and privacy safeguards. The vast majority of healthcare equipment is vulnerable to hacks, endangering patient data, and derisory management of life-support systems can significantly affect the course of a patient’s treatment. To address this problem, AI of Medical Thing (AIoMT) is being used to increase the high reliability and effectiveness of the healthcare system. AIoMT carries patient records, contacts, and other clinical records, and devices packed with clinical data. Even though these ubiquitous and affordable sensing technologies have the ability to change reaction therapy into preventive services, safety, and confidentiality problems are frequently a threat. IoMT system administration and security are likewise very challenging. This study explores several methods used for securing AIoMT devices and ensuring the privacy of data to address the security concerns preventing the use of AIoMT to safeguard patient information.
