Abstract: With the integration of medicine and engineering fields, machine learning is increasingly widely used in medicine. However, there are many problems in the current machine learning courses in medical colleges, such as the disconnection between the teaching content and the actual demand, the inflexibility of traditional teaching methods, and the lack of practical opportunities for students. To this end, a series of reform plans are proposed, including focusing on medical application scenarios, introducing interdisciplinary cooperation, innovating teaching methods, and strengthening practical links. Through the reform and practice, the learning enthusiasm of student is improved, the learning effect is remarkable, the interdisciplinary cooperation effect is obvious, and the employment competitiveness is enhanced. This paper aims to provide reference for the teaching reform of machine learning courses in medical colleges and promote the development of education under the background of medical industry integration.

Key words: Medical and industrial integration, Machine learning course, Teaching reform, Practical ability, Innovation ability, Interdisciplinary