explainable ai

AI based underwater ocean waste detection and classification: a comprehensive review, key issues and future direction

Time Series Forecasting in Construction Management: A Scientometric Analysis, Qualitative Review, and Future Research

The increasing availability of construction data and advances in artificial intelligence (AI) have accelerated the adoption of time series forecasting across construction management. However, a comprehensive understanding of the field’s knowledge structure, methodological evolution, and future directions remains limite...

Explainable Deep Learning Model for Predicting Overall Survival in Patients Receiving Palliative Radiotherapy for Bone Metastases

An explainable deep learning model was developed and evaluated, which predicted survival during the first year after radiotherapy with discrimination and calibration comparable to those of a Cox proportional hazards model, indicating that this prognostic information can be provided as a simple bedside score rather than...

Governing artificial intelligence in strategic communication: institutional enablement and communication effectiveness in digitally mediated environments

A socio-technical, governance-centered model examining how AI professional competency, organizational AI support, perceived value of AI and perceived AI-related risk relate to communication effectiveness among public relations professionals in the United Arab Emirates concludes that institutional enablement is the prin...

Microbiome and Metabolomics in Obesity: Advances in Understanding and Interventions Across the Lifespan.

Obesity arises from intertwined and reciprocal diet-microbiome-host pathways that reshape energy balance, insulin sensitivity, and inflammation. This review synthesizes mechanistic links between microbial functions and metabolic control, charts lifestyle-related lifecourse dynamics from birth to older age, examines how...

Intelligent Martial Arts Coaching Framework Using Artificial Intelligence for Real-Time Action Detection and Performance Feedback

MMAF-Net is proposed, a multi-branch deep learning architecture that integrates visual, pose-estimation and inertial sensor streams to extract complementary motion features, fused via a temporal attention module to classify 23 karate action types accurately.

A Study to Analyze the Role of Artificial Intelligence in Enhancing Customer Experience in Digital Marketing

The findings suggest that AI can meaningfully enhance digital customer experience when it is implemented as a supporting technology built around personalisation, convenience and responsiveness rather than as a replacement for human interaction.

AI-Driven Risk Management Optimization for Economic Resilience and Crisis Recovery

This chapter looks at how AI techniques including ML, DL, NLP and RL can be used in many fields, such as finance, operations, cybersecurity, and healthcare. It shows how AI makes predictive analytics better, speeds up decision-making, and makes dynamic response systems better while also cutting down on human mistakes a...

Voice-Based Screening of Depression and Anxiety Using Machine Learning and Deep Learning: A Scoping Review of Methods and Clinical Readiness

Despite the high global prevalence of depressive and anxiety disorders, access to early clinical assessment remains limited for many. Although this field has grown rapidly, existing reviews have focused primarily on technical performance, with limited systematic attention to whether current models meet the prerequisite...

Predicting Craniospinal Surgery in Pediatric Achondroplasia: Benchmarking Statistical Inference and Explainable AI Under Rare-Disease Constraints.

In a reproducible dual-stream benchmark, XAI improved discrimination over conventional inference by capturing clinically contextualized, complex nonlinear predictive dependencies and interactions associated with cranial and spinal surgical risk in achondroplasia using preoperative variables.

How to Build a Controlled AI Assistant for Quantum Computing

An architectural approach in which free-form dialogue is turned into a controlled computational workflow: the lifecycle stage determines the AI's goal, the context available to it, and the set of tools it is allowed to use right now. The user describes a task in ordinary language, the assistant translates it into a str...

How to Build a Controlled AI Assistant for Quantum Computing

An architectural approach in which free-form dialogue is turned into a controlled computational workflow: the lifecycle stage determines the AI's goal, the context available to it, and the set of tools it is allowed to use right now. The user describes a task in ordinary language, the assistant translates it into a str...