计算机科学
生成语法
领域(数学分析)
计算机安全
风险分析(工程)
数据科学
认知
医疗保健
人工智能
业务
心理学
政治学
数学分析
数学
神经科学
法学
作者
Zhen Ling Teo,Chrystie Wan Ning Quek,Joy Le Yi Wong,Daniel Shu Wei Ting
标识
DOI:10.1016/j.apjo.2024.100091
摘要
Generative Artificial Intelligence (GenAI) are algorithms capable of generating original content. The ability of GenAI to learn and generate novel outputs alike human cognition has taken the world by storm and ushered in a new era. In this review, we explore the role of GenAI in healthcare, including clinical, operational, and research applications, and delve into the cybersecurity risks of this technology. We discuss risks such as data privacy risks, data poisoning attacks, the propagation of bias, and hallucinations. In this review, we recommend risk mitigation strategies to enhance cybersecurity in GenAI technologies and further explore the use of GenAI as a tool in itself to enhance cybersecurity across the various AI algorithms. GenAI is emerging as a pivotal catalyst across various industries including the healthcare domain. Comprehending the intricacies of this technology and its potential risks will be imperative for us to fully capitalise on the benefits that GenAI can bring.
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