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Big Data Integration and Artificial Intelligence in Medical Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 December 2025 | Viewed by 28

Special Issue Editors


E-Mail Website
Guest Editor
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 610000, China
Interests: intelligent processing of signals and information; health informatics; big data analytics in medicine; clinical decision support systems; artificial intelligence in healthcare

E-Mail Website
Guest Editor
School of Electronics, Peking University, Beijing 100871, China
Interests: electronic and communication engineering; biophysics and bioelectronics; artificial intelligence and big data analytics in medicine; medical equipment

Special Issue Information

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

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence in healthcare
  • big data analytics in medicine
  • clinical decision support systems (CDSS)
  • multimodal data fusion
  • deep learning in medical imaging
  • federated learning in healthcare
  • explainable AI (XAI)
  • predictive modeling in healthcare
  • health informatics
  • personalized and precision medicine
  • synthetic data generation in healthcare
  • privacy-preserving machine learning
  • wearable health technology
  • natural language processing in clinical data
  • cloud computing in health data management
  • real-time health monitoring systems
  • generative AI in medical applications
  • medical Internet of Things (IoT)
  • electronic health record (EHR) integration
  • AI-driven drug discovery

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Published Papers

This special issue is now open for submission.
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