Building Fast and Secure Deep Learning-Driven Applications in Healthcare

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

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• healthcare
• robotics
• edge device
• security