<![CDATA[Where Artificial Intelligence is most active today, there are quite a few applications of AI in the sphere of healthcare – never before have diagnostics, treatment, decision making have been so precise, effective, and individual. However in the actual application of artificial intelligence in healthcare systems, one is bound to encounter a number of issues such as cybersecurity and issues to do with secure access to information. The most vulnerable type of personal health information in this regard is the electronic personal health information as patient data can be hacked though data breach, ransom ware, or alteration of the algorithm used by the AI system to the detriment of the patient in question and that of the system in general. Further, there is an enforceable obligation for integrated and smart access to knowledge for clinicians and researchers and strong patient demand for patient protection and patient data privacy. In this opinion presentation, this review looks at the two elements of cybersecurity conflict as well as information availability in an AI-focused healthcare environment. They announce threats of raised levels of security risks, network vulnerabilities, and data and algorithms manipulation. The paper also includes the possibility of combating such challenges, such as; AI security tools, encryption and authentication, and integrating federated learning, the block chain, and priory-preserving AI. Further, it has recognized the importance of the expansion of consideration about how data is passed from one entity to another with no disruptions, the patient-level approach to data management, and cybersecurity training for the, respectively, healthcare workforce.]]>
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