explainable ai

Developing a Federated, Lightweight, Interpretable, and Specialized AI-Based Intrusion Detection System for Medical Internet of Things (IoMT) Environments

The rapid expansion of the Internet of Medical Things (IoMT) has enhanced healthcare services, but it has also exposed these systems to a growing range of cyberattacks. Addressing this challenge requires effective intrusion detection solutions. Machine learning-based intrusion detection systems (IDSs) offer a promising...

AI Governance Frameworks for Privacy-Preserving Intelligent Systems: Integrating Trust, Compliance, and Secure Data Architectures

The analysis suggests that governance frameworks succeed when privacy-preserving technologies are embedded into system architecture from the outset rather than added afterward, when compliance obligations are translated into measurable technical requirements, and when trust is treated as an emergent property of verifia...

A study on AI-enabled course development, AI proficiency, and first-year students’ academic and psychological adjustment

Background The rapid integration of digital technologies and generative artificial intelligence (AI) into higher education has reshaped first-year students’ learning experiences and self-reported psychological adjustment. Using a cross-sectional self-report design, this study examined the statistical associations among...

Artificial Intelligence-Related Risks in Interventional Pulmonology: An Exploratory Enumeration and Ranking Study Across Five General-Purpose Large Language Models

Background/Objectives: Artificial intelligence (AI) is entering interventional pulmonology (IP) faster than its potential risks have been systematically catalogued. We explored whether general-purpose large language models (LLMs), now widely consulted informally by patients and clinicians, could provide a rapid and str...

Applications, Safety Challenges and Future Directions of AI Agents in Cardiovascular Prediction: A Review of Technological Evolution, System Architecture and Clinical Translation

Cardiovascular disease remains a major contributor to mortality and long-term morbidity worldwide. For this reason, risk prediction, early detection, and decision support have become central tasks in digital health research. Cardiovascular prediction has developed from statistical scores to machine learning and deep le...

A systematic review and Zero Trust governance framework for agentic UAV robotics in public safety

It is argued that trustworthy public-safety UAV robotics requires verifying not only who controls a robot, but also whether its own reasoning, tool use, and evidence handling can be trusted.

Explainable optimized deep learning and generative AI based framework for finger millet disease detection in smart agriculture

The integration of DL, XAI, and generative AI provides a scalable approach for detecting and managing finger millet diseases and boosts precision agriculture by providing AI-based and XAI-supported decision-making, while fostering sustainable agricultural practices.

The ethics-driven data governance framework for health-based AI (EDG-AI4H): an integrated approach for empowering explainable AI in health insurance risk prediction in Iran

Geospatial Artificial Intelligence (GeoAI) for Sustainable Urban Governance: A Systematic Review and Governance-Oriented Framework

GeoAI has advanced the analysis and prediction of urban systems by integrating GIS with artificial intelligence, yet its contribution to urban planning and governance remains limited. Many applications function as black-box predictive tools, making results difficult to interpret, justify, audit, and use in formal plann...

From Context to Plasticity: A Three-Timescale Architecture for Persistent Memory and Recursive Online Learning

This work presents a theoretical architecture for continually adapting AI systems organized around three distinct timescales: (1) fast transformer key-value context for immediate interaction, (2) medium-term persistent recurrent memory with decaying importance and consolidation, and (3) slow, controlled parameter adapt...

AI Meets Analytical Chemistry: The Next Era of Food Forensics

Food fraud and adulteration continue to threaten food safety, consumer confidence and international trade. The challenges of investigating food-forensics reliably are compounded by increasingly complex supply chains, changing deceptive practices and difficulties in interpreting high-dimensional analytical data. The rev...

Why the User Rages: A User-Centered Study on Conversational AI Models' Defensive Communication Behaviors and Their Effects

On August 8 (UTC+8), 2025, OpenAI rolled out GPT-5 to the public, and simultaneously removed access to all “legacy models” including GPT-4o. This action led to a global movement to “bring back GPT-4o”. The protest against “cold and detached” GPT-5 revealed users’ acute sensitivity to anthropomorphic AI responses: users...