Explainable Artificial Intelligence for Disease Detection and Secure Monitoring Systems
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms and Mathematical Models for Computer-Assisted Diagnostic Systems".
Deadline for manuscript submissions: 30 September 2025 | Viewed by 234
Special Issue Editor
Special Issue Information
Dear Colleagues,
Health represents a holistic state of physical, mental, and social well-being, not just the absence of illness. Artificial intelligence (AI) has recently become a transformative tool in healthcare, particularly in disease detection, remote monitoring, and personalised care. AI aids in early disease identification, tracking patient health, and tailoring interventions, proving highly effective in supporting medical diagnoses. However, many AI systems function as "black boxes", offering results without clear explanations. This lack of transparency raises concerns among clinicians, who rely on interpretable evidence for decision making, resulting in scepticism and limiting AI's integration into clinical workflows.
To overcome this, innovative methods are needed to improve the explainability of AI systems in healthcare. Explainable deep learning (DL) techniques can address this by clarifying AI-driven diagnoses, building trust among patients and physicians, and promoting broader adoption in medical practice.
This Special Issue focuses on advancements in explainable AI (XAI) for secure healthcare. Contributions are invited on theoretical developments, novel frameworks, and practical applications of XAI in disease detection, secure remote monitoring, and personalised care, encompassing both conventional and pioneering approaches. The Special Issue focuses on the following topics and more.
- Disease detection methods based on XAI methodologies;
- XAI-enabled tumour detection and diagnosis;
- Novel challenges in current XAI-driven health systems;
- XAI in cardiovascular and neurological disease diagnosis;
- XAI-driven models for infectious disease monitoring;
- Human-centric AI for disease diagnosis;
- The impact of XAI on clinical decision support systems;
- Integrating XAI with IoT-based health monitoring devices;
- XAI-driven early warning systems for chronic conditions;
- Explainable AI for secure IoT-enabled remote health monitoring;
- Privacy-preserving explainable models for healthcare monitoring systems;
- Explainable AI for cybersecurity in connected healthcare systems.
Dr. Qurat-Ul-Ain Mastoi
Guest Editor
Manuscript Submission Information
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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. Algorithms 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
- explainable AI
- disease detection
- secure healthcare
- healthcare monitoring
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