Building Fast and Secure Deep Learning-Driven Applications in Healthcare

A special issue of AI (ISSN 2673-2688).

Deadline for manuscript submissions: 15 April 2026 | Viewed by 13

Special Issue Editors

Computer Engineering, University of Houston–Clear Lake, Houston, TX, USA
Interests: wireless communication; intelligent sensor systems; wireless healthcare
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Guest Editor
Computer Science, University of Houston-Downtown, Houston, TX, USA
Interests: body sensor networks; machine learning; intelligent systems; Internet of Things; virtual reality
Electrical & Biomedical Engineering, University of Nevada, Reno, NV, USA
Interests: power electronics; renewable energy; energy conversion; power system; smart grid; motor control; electric vehicle; reinforcement learning; deep learning

Special Issue Information

Dear Colleagues,

Deep learning (DL) has made remarkable progress in image, video, and language processing, including generative Artificial Intelligence (AI) like ChatGPT. In healthcare, DL models assist in medical imaging (e.g., MRI and X-ray analysis), disease prediction, surgical/rehabilitation robotics, drug discovery, virtual health assistants, and personalized treatment plans. The benefits include improved accuracy, enhanced efficiency, personalized medicine, and remote care. However, challenges and obstacles currently hinder the application of deep learning-based technologies in healthcare.

  1. Computational Speed: Fast and secure hardware is essential for real-time processing of healthcare data.
  2. Data Security and Privacy: Sensitive patient data must be protected from breaches.
  3. Model Robustness: The DL model must be resilient against adversarial attacks and noisy data.

Recently, research has addressed these issues through the following means:

  1. Edge AI: Enables decentralized, privacy-preserving model training.
  2. Lightweight Neural Networks: Reduce computational overhead for faster inference.
  3. Trustworthy Machine Learning at the Network Edge: The deployment of ML at the edge demands rigorous attention to security. 

We are pleased to invite you to submit your research article to this Special Issue by 31 January 2026. This Special Issue not only consolidates recent research but also provides a roadmap for scalable, secure, and efficient DL implementations in critical industries such as healthcare. 

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Intelligent Assistive Robot applications;
  • Low-cost, low-power hardware design in DL;
  • Real-time processing for healthcare applications;
  • AI-powered virtual healthcare. 

We look forward to hearing from you.

Dr. Jiang Lu
Dr. Ting Zhang
Dr. Xingang Fu
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. AI is an international peer-reviewed open access monthly 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 1600 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

  • healthcare
  • robotics
  • edge device
  • security

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Published Papers

This special issue is now open for submission.
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