Big Data Integration and Artificial Intelligence in Medical Systems

Dear Colleagues,

In recent years, the convergence of big data technologies and artificial intelligence (AI) has ushered in a new era of medical systems—comprehensive, data-driven frameworks encompassing clinical diagnostics, decision support, treatment management, patient engagement, and healthcare service delivery. This Special Issue aims to highlight the most recent advances in medical system intelligence through the integration of heterogeneous medical data and state-of-the-art computational methods.

We particularly encourage submissions that address the challenges in multi-modal data fusion, machine learning models for disease detection and decision support, real-time monitoring solutions, and interpretable AI in clinical settings. Articles that present applications of deep learning, federated learning, generative models, and privacy-aware computation to medical tasks—especially those with validated impact on the healthcare delivery—are highly welcomed.

This Special Issue seeks to foster a multidisciplinary perspective that bridges data science and medicine by showcasing effective methodologies, robust frameworks, and scalable implementations. We also encourage the use and creation of open-access datasets and reproducible benchmarks that advance collaborative research in AI-enabled medical systems. The ultimate objective is to deepen our understanding of current capabilities and future opportunities in building intelligent, interoperable, and trustworthy healthcare solutions.

Dr. Liaoyuan Zeng
Dr. Yiming Lei
Guest Editors

Manuscript Submission Information

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