Mental Health Challenges Among Chinese Art Students: A Critical Review of Body Image, Social Comparison, and Academic Stress

2025-07-30T14:34:51+00:00

Mental health issues among university students in China have become increasingly prominent, particularly within specialized disciplines such as art education, where students face unique psychological challenges. This critical review explores the mental health landscape of Chinese art students, with a focus on three major contributing factors: body image dissatisfaction, social comparison, and academic stress. Using a narrative review approach, relevant literature from peer-reviewed journals, government reports, and academic databases was analyzed to understand how these stressors intersect and impact student well-being. The findings indicate that body image concerns are intensified by aesthetic expectations within art environments and exacerbated by exposure to idealized imagery on social media. Social comparison, both offline and online, further contributes to self-esteem issues, anxiety, and perfectionism. Meanwhile, academic pressure related to competitive evaluations, performance-based assessments, and career uncertainty imposes additional mental burdens. The combined influence of these factors creates a high-risk psychological environment for art students in China. This review highlights the urgent need for culturally sensitive mental health interventions, increased institutional support, and future research that addresses these intersecting challenges. The implications extend to art educators, mental health professionals, and policymakers seeking to promote emotional well-being in creative education contexts

A Review of Artificial Intelligence-Assisted Diagnostic Imaging Tools in the Detection and Characterization of Brain Tumors

2025-10-07T17:28:28+00:00

Background:
Brain tumors represent a diverse group of central nervous system neoplasms that require precise diagnosis and characterization for effective treatment. Advances in neuroimaging have improved the detection of these tumors; however, conventional interpretation methods remain time-intensive and subject to variability. Artificial intelligence (AI), particularly through machine learning and deep learning, has emerged as a powerful tool in neuro-oncological imaging, offering automation, consistency, and enhanced diagnostic performance.

Objective:
This review aims to provide a comprehensive overview of AI-assisted imaging tools used in the detection and characterization of brain tumors. It highlights key AI technologies, their clinical applications, performance compared to human experts, and the emerging trends shaping the future of AI in neuro-oncology.

Methods:
A narrative review was conducted of recent peer-reviewed studies focused on the application of AI in brain tumor imaging. Emphasis was placed on machine learning and deep learning models used for tumor segmentation, histopathologic and molecular subtype prediction, prognostic modeling, and treatment response monitoring. Technical challenges, ethical concerns, and regulatory considerations were also examined.

Results:
AI models have demonstrated high accuracy in tasks such as tumor segmentation, classification of tumor types and grades, non-invasive prediction of molecular markers (e.g., IDH mutation, MGMT methylation), and survival prediction. Emerging techniques such as federated learning, multimodal data integration, and explainable AI are addressing key limitations, including data privacy, generalizability, and clinical trust.

Conclusion:
AI-assisted imaging holds considerable promise in improving the accuracy, speed, and personalization of brain tumor diagnosis and management. For widespread clinical adoption, future efforts should focus on multi-institutional collaboration, prospective validation, regulatory alignment, and clinician education. With continued advancement, AI can become a valuable adjunct in the neuro-oncology diagnostic arsenal, ultimately contributing to better patient outcomes.

Peta International Journal of Public Health

Mental Health Challenges Among Chinese Art Students: A Critical Review of Body Image, Social Comparison, and Academic Stress

A Review of Artificial Intelligence-Assisted Diagnostic Imaging Tools in the Detection and Characterization of Brain Tumors