“Artificial intelligence and medical image” is an auxiliary tool for the computer to complete image classification, target detection, image segmentation, and retrieval and assist doctors in diagnosing and treatment based on medical image through deep learning. This chapter includes the review of Artificial intelligence (AI) and its application in radiology, pathology, eye disease, deontology, dermatology, and ophthalmology, which we have benefited from the use of AI methods. Modern medicine is evidence-based medicine based on experiments. Doctors' diagnosis and treatment conclusions must be based on corresponding diagnostic data. Imaging is an important part of diagnosing, and 80% to 90% of data in the medical industry are derived from medical imaging. Therefore, clinicians have a strong demand for images, and they need to conduct a variety of quantitative analyses of medical images and comparison of historical images to complete a diagnosis. In contrast to this qualitative reasoning, AI is good at identifying complex patterns in the data and providing quantitative assessments in an automated manner. Integrating AI into clinical workflows as a tool to assist physicians allows for more accurate and repeatable radiological assessments.