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Technologies
Special Issues
AI-Enabled Smart Healthcare Systems
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AI-Enabled Smart Healthcare Systems

A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Assistive Technologies".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 982

Special Issue Editors

Dr. Umer Saeed

E-Mail Website
Guest Editor
School of Computer Science and Technology, University of Bedfordshire, University Square, Luton LU1 3JU, UK
Interests: artificial intelligence in healthcare; machine learning for anomaly detection; sensor fault diagnosis in wireless networks; human activity recognition; non-invasive respiratory monitoring
Prof. Dr. Luc de Witte

E-Mail Website
Guest Editor
Center of Expertise Health Innovation, The Hague University of Applied Science, 2521 EN Den Haag, The Netherlands
Interests: assistive technology service delivery; care robotics; digital healthcare solutions; technologies applied to global health challenges
Dr. Haipeng Liu

E-Mail Website
Guest Editor
Centre for Intelligent Healthcare, Coventry University, Coventry CV1 5RW, UK
Interests: computational simulation of the cardiovascular system; AI-assisted diagnosis; medical data analysis; wearable sensors
Special Issues, Collections and Topics in MDPI journals
Dr. Sana Ullah Jan

E-Mail Website
Guest Editor
School of Computing Engineering and the Built Environment, Edinburgh Napier University, Edinburgh EH10 5DT, UK
Interests: artificial intelligence; machine learning; cyber security; intrusion detection systems; information security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Rapid advancements in artificial intelligence (AI) have revolutionized healthcare by enabling innovative solutions for patient care, diagnostics, and operational efficiency. This Special Issue focuses on exploring cutting-edge AI technologies, methodologies, and systems that address challenges in smart healthcare. We invite contributions that highlight the integration of AI in healthcare, encompassing areas such as predictive analytics, personalized medicine, remote monitoring, decision support systems, and robotics-assisted care. Research addressing the ethical considerations, data privacy, and security in AI-enabled healthcare systems is also welcome. Our aim is to foster an interdisciplinary dialogue to advance the development and adoption of AI solutions for improving healthcare outcomes, operational excellence, and patient experiences.

Dr. Umer Saeed
Prof. Dr. Luc de Witte
Dr. Haipeng Liu
Dr. Sana Ullah Jan
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. Technologies 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

  • artificial intelligence
  • smart healthcare systems
  • predictive analytics
  • personalized medicine
  • remote monitoring
  • decision support systems
  • robotics in healthcare
  • data privacy in artificial intelligence
  • ethical artificial intelligence in healthcare
  • healthcare automation

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Published Papers (1 paper)

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Research

18 pages, 3219 KB  
Article
Designing Trustworthy AI Systems for PTSD Follow-Up
by María Cazares, Jorge Miño-Ayala, Iván Ortiz and Roberto Andrade
Technologies 2025, 13(8), 361; https://doi.org/10.3390/technologies13080361 - 15 Aug 2025
Viewed by 394
Abstract
Post-Traumatic Stress Disorder (PTSD) poses complex clinical challenges due to its emotional volatility, contextual sensitivity, and need for personalized care. Conventional AI systems often fall short in therapeutic contexts due to lack of explainability, ethical safeguards, and narrative understanding. We propose a hybrid [...] Read more.
Post-Traumatic Stress Disorder (PTSD) poses complex clinical challenges due to its emotional volatility, contextual sensitivity, and need for personalized care. Conventional AI systems often fall short in therapeutic contexts due to lack of explainability, ethical safeguards, and narrative understanding. We propose a hybrid neuro-symbolic architecture that combines Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), symbolic controllers, and ensemble classifiers to support clinicians in PTSD follow-up. The proposal integrates real-time anonymization, session memory through patient-specific RAG, and a Human-in-the-Loop (HITL) interface. It ensures clinical safety via symbolic logic rules derived from trauma-informed protocols. The proposed architecture enables safe, personalized AI-driven responses by combining statistical language modeling with explicit therapeutic constraints. Through modular integration, it supports affective signal adaptation, longitudinal memory, and ethical traceability. A comparative evaluation against state-of-the-art approaches highlights improvements in contextual alignment, privacy protection, and clinician supervision. Full article
(This article belongs to the Special Issue AI-Enabled Smart Healthcare Systems)
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