explainable ai

Artificial Intelligence and Machine Learning for Road Traffic Congestion Prediction and Forecasting: A Systematic Review of Methods, Validation, Explainability, and Reproducibility

Artificial intelligence (AI) and machine learning (ML) are increasingly applied to road traffic congestion prediction, but heterogeneous outcomes, models, horizons, and evaluation practices limit comparability. The objective of this study was to synthesize methods, applications, validation, explainability, and reproduc...

The Financial Sector

This chapter examines the relationship between AI and the UK financial sector, focusing on the opportunities, risks, and regulatory challenges arising from increasing AI adoption. It begins by outlining the significance of the financial sector within the UK economy and society, emphasising its role in supporting econom...

Integrating Artificial Intelligence into Orthopedic Practice: Modeling Attitudes and Intentions to Use AI

Background/Objectives: Artificial intelligence is increasingly used in medicine, particularly in orthopedics, to support medical image interpretation, diagnosis, clinical decision-making, and treatment selection. Its integration into clinical practice depends largely on doctors’ perceptions and attitudes toward this te...

Responsible AI for Acute Stroke Management.

This review synthesizes the current literature on explainable artificial intelligence and fairness in artificial intelligence applications for acute stroke management, identifies persistent challenges, and outlines recommendations for the development of equitable and trustworthy systems in stroke care.

A medically grounded LLM agent–based tool to detect patient safety events in medical records

SAFE–AI (Structured and Automated Framework for Explainable AI), a novel method for clinical decision making that combines the strengths of clinical expert knowledge with LLMs in an ontology–driven model that minimizes hallucinations using strict rules, is presented.

Elaborating Explainable AI for Software Fault Prediction: Interpretability Techniques and Performance Insights

Modeling the pathway from transformational leadership to innovative work behavior via AI readiness: advancing SDG 4 and SDG 8 in Indonesian higher education

Drawing on a cross-sectional survey of 250 lecturers and administrative staff from Indonesian higher education institutions (HEIs), this study examined the statistical relationships among transformational leadership, AI readiness, and innovative work behavior (IWB) using partial least squares structural equation modeli...

Automatic and User-Centered Evaluation of an AI-Driven Korean Recipe RAG Chatbot: Alignment, Mismatch, and Actionability

The findings suggest that the two RAGAS metrics do not, on their own, fully explain user-perceived quality when evaluating recipe RAG systems, and that query-type-specific analysis and user-centric evaluation should be considered together.

Development of an Explainable AI-Driven Algorithm for the Analysis and Verification of Voice Recording Authenticity

How Achievement Emotions and Grit Affect Learners' Psychological Well‐Being in AI ‐Based Language Education: A Bifactor Analysis

The presentation of Artificial Intelligence (AI) within educational settings has changed the conventional learning settings to advanced tools that improve the students' academic achievement. Psychological Well‐being (PWB) is a critical element of students' achievement in AI‐based settings. In AI‐based language learni...

From surveillance to intelligence: a scoping review of machine learning for antimicrobial resistance surveillance intelligence across One Health

A One Health AMR Surveillance Intelligence Framework is proposed to organise this shift from data generation toward actionable, adaptive surveillance intelligence, and the evidence demonstrates technical feasibility far more convincingly than operational readiness.

Attribution, zonation, and simulation of spatiotemporal distribution of negative oxygen ions in mountainous megacity: A case study of Chongqing, China

Negative oxygen ions (NOI) are key indicators of urban ecological quality. However, NOI dynamics in mountainous megacities remain poorly understood. A key challenge lies in translating complex environmental observations into interpretable knowledge for environmental planning rather than prediction alone. Therefore, we...