explainable ai

Integration of multispectral imaging and explainable AI for alfalfa seed priming optimization under saline-alkali stress

Soil salinization poses an increasingly severe threat to sustainable agriculture globally, while conventional seed priming optimization remains time- and resource-intensive, limiting its widespread adoption. This study developed an innovative smart seed priming framework that seamlessly combined multispectral imaging t...

Deep Meta-Learner Stacking with Explainable AI for Vision-Based Plastic Waste Classification

This work introduced a vision-based waste classification system that relies on Deep Meta-Learner Stacking with Explainable AI (DMLSE) to merge the unique feature representations of a BasicCNN, VGG16, ResNet50V2, and MobileNetV2 across the synthetic, garbage, and waste classification datasets.

Editorial: Enhancing gait therapy with artificial intelligence: current trends and future prospects

Impaired mobility is among the most common impairments caused by neurologic, neurodegenerative, and orthopaedic disorders. Depending upon the cause being stroke, Parkinson's disease, spinocerebellar ataxia, or osteoarthritis needing arthroplasty, the disruption in gait and mobility causes dependency, increased risk of...

Smart Loyalty Programs and Consumer Retention in E-Commerce Platforms

Smart Loyalty Programs, Consumer Retention, E-Commerce, AI Personalisation, Gamification, Emotional Loyalty, Customer Lifetime Value, Structural Equation Modeling, Switching Cost, Reward Redemption ABSTRACT The evolution of loyalty programs from simple point-accumulation schemes to intelligent, technology-driven retent...

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

Autonomous Unmanned Aerial Vehicle (UAV) robotic systems are increasingly deployed in safety-critical public-safety environments, including emergency response, search and rescue, infrastructure inspection, traffic incident assessment, and drone-as-first-responder (DFR) operations. At the same time, the supporting AI is...

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