  Artificial intelligence (AI) methods hold immense potential to revolutionize
numerous medical care by enhancing the experience of medical experts and
patients. AI-based computer-assisted diagnosis and treatment tools can
democratize healthcare by matching the clinical level or surpassing clinical
experts. As a result, advanced healthcare services can be affordable to all
populations, irrespective of demographics, race, or socioeconomic background.
The democratization of such AI tools can reduce the cost of care, optimize
resource allocation, and improve the quality of care. In contrast to humans, AI
can uncover complex relations in the data from a large set of inputs and even
lead to new evidence-based knowledge in medicine. However, integrating AI into
healthcare raises several ethical and philosophical concerns, such as bias,
transparency, autonomy, responsibility, and accountability. Here, we emphasize
recent advances in AI-assisted medical image analysis, existing standards, and
the significance of comprehending ethical issues and best practices for
clinical settings. We cover the technical and ethical challenges and
implications of deploying AI in hospitals and public organizations. We also
discuss key measures and techniques to address ethical challenges, data
scarcity, racial bias, lack of transparency, and algorithmic bias and provide
recommendations and future directions.
