explainable ai

XAI-OPL Risk Prediction Dataset — 31 Studies on AI/ML for Occupational Postural and Lumbar Risk

This dataset is the complete reproducibility package accompanying the systematic review and meta-analysis "Explainable and interpretable machine learning for occupational postural and lumbar risk prediction: A systematic review and meta-analysis" (PROSPERO registration: CRD420261530250). The review is, to our knowledge...

Explainable AI Techniques for Intrusion Detection Systems

The proliferation of interconnected digital systems, cloud infrastructures, Internet of Things (IoT) devices, industrial control systems, and cyber-physical infrastructures has led to a growth in the complexity of cyber security environments. MLand DL integrated into modern IDSs to identify complex activities in the tr...

Foundations of Consecutive Interpreting: For EFL University Students

Foundations of Consecutive Interpreting: For EFL University Students introduces consecutive interpreting through Arabic–English and English–Arabic teaching cases for Arabic-speaking EFL university students across the Arab world. It connects understanding spoken messages with accountable oral performance. Modern Standar...

Integrated allometric scaling, physicochemical profiling, and random forest modelling for predicting antioxidant compounds in sweeteners from overripe Malaysian bananas

Abstract Bananas ( Musa spp. ) are rich in bioactive compounds that are essential for health, including support for digestion, immunity, and sustained energy. This research compared the nutritional profiles, physicochemical properties, determinants of antioxidant compounds, and antioxidant activities of sweeteners from...

ARTIFICIAL INTELLIGENCE IN FINANCIAL STATEMENT FRAUD DETECTION: A CRITICAL SYNTHESIS OF EMERGING TRENDS, METHODOLOGIES, AND FUTURE DIRECTIONS FOR U.S. PUBLICLY TRADED COMPANIES

Financial statement fraud causes systemic damage to U.S. capital markets, investor confidence, and the credibility of public company disclosures. Artificial intelligence (AI) offers promising new detection capabilities, yet its evidence base and operational readiness remain unevenly developed across the literature. Thi...

Human-Centered AI and Decision Support in Security Operations Centers

The growing complexity of cyber threats has made Security Operations Centers (SOCs) essential for real-time threat detection, incident response, and infrastructure protection. However, traditional black-box AI models often reduce trust and transparency in cybersecurity decisions. This chapter explores human-centered Ex...

Machine Learning in E-Commerce: Trends, Applications, and Future Challenges

E-commerce platforms continuously generate large amounts of data from customer searches, browsing activities, purchases, reviews, and delivery operations. Machine learning (ML) turns this data into useful predictions and decisions that improve product recommendations, pricing, fraud detection, inventory management, and...

Real-Time Dynamic Pricing and Revenue Management in Hospitality 5.0

This chapter discusses upgrades in pricing strategies for the hospitality industry. It will analyze real-time dynamic pricing and advanced revenue management systems with reference to the framework of Hospitality 5.0. AI, IoT, and data analytics help to advance pricing strategies from basic static models to cutting-edg...

Measuring University Students' Ethical Judgments of Generative AI Use: Development and Initial Validation of Four Instruments for Academic Integrity Research

Designing responsible AI feedback in higher education: faculty readiness, student judgement, and metacognitive calibration

Artificial intelligence (AI) is now part of everyday academic work in higher education, including feedback. However, AI feedback does not automatically lead to learning. It can help students rethink a concept, improve a draft, and notice gaps in their work, but it can also create a false sense of progress when students...

From Human Judgment to Machine Learning: A Philosophical Study of Knowledge Creation in Modern Accounting

Background: The integration of artificial intelligence (AI) and machine learning into accounting and auditing has transformed the creation, validation, and application of professional knowledge, raising questions about the legitimacy of algorithmic knowledge in accounting practice. Objective: This study examines the ep...

Diagnostic Performance of Deep Learning Models for Ocular Toxoplasmosis Using Fundus Photography: A Systematic Review and Meta-Analysis.

BACKGROUND Ocular toxoplasmosis (OT) is the leading infectious cause of posterior uveitis worldwide, yet diagnosis remains challenging without a universal gold standard. Although deep learning (DL) shows significant promise for automated image analysis, a rigorous synthesis of its diagnostic accuracy across heterogeneo...