The rapid development of artificial intelligence in the field of healthcare has greatly improved diagnosis accuracy, disease prediction, personalized treatment and healthcare resource management. However, with the widespread application of medical artificial intelligence, challenges has emerged in the aspects of medical data, model development and evaluation, and societal considerations. Therefore, this study aims to explore challenges in the application of artificial intelligence in healthcare and suggest a series of feasible solutions to improve medical professional and researchers' understanding of medical artificial intelligence and enhance the quality of healthcare in clinical practice.