ABSTRACT
Artificial intelligence (AI) technologies are facilitating the work of modern healthcare organisations to leverage the power of big data in clinical practice. In most cases, AI-based systems improve clinical decision-making using multiple layers of information and pre-specified algorithms. In addition, recent AI technologies like machine learning can learn from existing data and perform predictive operations resulting in a robust performance in clinical settings (1, 2). Such innovations are likely to serve the healthcare industry by minimising human error, savings costs, and maximising informed decision-making. However, critical challenges may affect the applications of AI in clinical settings, which include the effects on patient-provider communication, safety and efficacy of health services, and humane aspects of caregiving.