Submission Deadline: 31 January 2027 View: 36 Submit to Special Issue
Prof. Dr. Ramiro Barbosa
Email: rsb@isep.ipp.pt
Affiliation: Electrical Engineering, Instituto Superior de Engenharia do Porto (ISEP), Polytechnic of Porto, Porto, Portugal
Research Interests: modeling, control, simulation, fractional calculus, artificial intelligence, evolutionary algorithms, robotics
Dr. Luís Conceição
Email: msc@isep.ipp.pt
Affiliation: GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, ISEP, Polytechnic of Porto, Porto, Portugal
Research Interests: artificial intelligence in healthcare, clinical decision support systems, digital health, remote patient monitoring, wearable health technologies, healthcare data science, generative AI, explainable and trustworthy AI, privacy-preserving AI, human-in-the-loop AI, ethical and regulatory challenges in healthcare AI
Dr. Júlio Cesar Botelho de Souza
Email: jbs@isep.ipp.pt
Affiliation: GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, ISEP, Polytechnic of Porto, Porto, Portugal
Research Interests: artificial intelligence, digital health, health services research, public health, clinical coding, data quality, biomedical ontologies
Artificial Intelligence (AI) is transforming healthcare by enabling new approaches to diagnosis, prognosis, treatment planning, patient monitoring, clinical decision support, and health service delivery. Recent advances in machine learning, deep learning, generative AI, natural language processing, medical image analysis, robotics, and wearable technologies are creating unprecedented opportunities to improve the quality, efficiency, accessibility, and personalization of healthcare. However, the integration of AI into real clinical environments also raises important scientific, technical, ethical, legal, and regulatory challenges, including data quality, interoperability, privacy, explainability, bias, robustness, accountability, trust, and clinical validation.
This Special Issue aims to provide a multidisciplinary forum for researchers, clinicians, engineers, data scientists, and healthcare stakeholders to present original research, reviews, and practical case studies on the development, evaluation, and responsible adoption of AI-based solutions in healthcare. Contributions are expected to address both methodological advances and real-world applications, with particular attention to clinical relevance, trustworthy AI, human-centred design, and future directions for safe and effective deployment.
Suggested themes include, but are not limited to, AI-enabled smart wearable and remote monitoring systems, generative AI and foundation models, machine learning and deep learning, diagnostic and prognostic AI, clinical decision support, healthcare data science, medical imaging and biomedical signal analysis, NLP for clinical text, healthcare robotics, explainable AI, human-in-the-loop AI, privacy-preserving AI, blockchain for healthcare data security, and ethical, legal, and regulatory challenges.
Potential topics include, but are not limited to the following:
· AI-enabled Smart Wearable and Remote Monitoring Systems
· Generative AI and Foundation Models in Healthcare
· Machine Learning and Deep Learning for Healthcare Applications
· Reinforcement Learning for Personalized and Adaptive Healthcare
· AI-based Diagnosis, Prognosis and Clinical Decision Support
· Healthcare Data Science and Predictive Analytics
· AI for Medical Imaging and Biomedical Signal Analysis
· Natural Language Processing for Clinical Text and Electronic Health Records
· Multimodal AI in Healthcare
· AI for Personalized and Precision Medicine
· Synthetic Data Generation for Healthcare AI
· Federated Learning and Privacy-Preserving AI
· Healthcare Robotics, Automation and Assistive Technologies
· AI-based Risk Prediction and Early Warning Systems
· Explainable and Interpretable AI for Clinical Decision Support
· Human-in-the-Loop and Human-Centred AI in Healthcare
· Human-AI Collaboration and Clinical Workflow Integration
· Trustworthy, Robust and Responsible AI in Healthcare
· AI Safety, Bias and Fairness in Healthcare
· Validation, Benchmarking and Clinical Evaluation of AI Systems
· Ethical, Legal, Privacy and Regulatory Challenges of AI in Healthcare
· Blockchain and Distributed Ledger Technologies for Secure Healthcare Data Management
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