This study explores how digital platforms can empower traditional mental health work models to address precision challenges such as delayed warning and generalized services in psychological support for international medical students in China. Taking the application of Wenzhou Medical University's "Zhejiang Ideological and Political Education" platform as a case, a mixed-methods approach was adopted. First, the core functions and workflow of the platform in dynamic management of mental health records, three-tier risk classification, and dynamic tracking were systematically analyzed. Second, quantitative data from three dimensions—early identification rate, warning response time, and intervention measure matching degree—were compared before and after the platform's deep application (2024 vs. 2025). Finally, through in-depth interviews and policy text analysis, the ethical boundaries in digital practice were examined. The application of the digital platform increased the early identification rate of psychological issues from 75.6% to 89.2%; the average response time for high-risk cases from anomaly detection to professional assessment was shortened from 5.2 days to 2.1 days; and the matching degree of intervention plans based on data analysis improved significantly. Meanwhile, the study clarified the operational pathways of key ethical principles such as "minimum necessary data collection," "informed consent," and "encryption and desensitization" in practice. The conclusion indicates that digital platforms can significantly enhance the precision and timeliness of psychological support for international medical students by enabling data-driven risk stratification and intelligent resource matching. However, their application must be built upon a solid ethical framework and institutional safeguards to balance technological efficacy with humanistic care.