explainable ai

Balancing the Triad: Socio-Technical Misalignments Between User-Centered Design, Agile, and AI in Healthcare Software

The rapid integration of Artificial Intelligence (AI) into healthcare software introduces profound complexities when combined with Agile Software Development (ASD) and User-Centered Design (UCD). Instead of a cohesive triad, this landscape exhibits partial intersections and fragmented literature. This Systematic Litera...

Non-extensive statistics of the glioblastoma transcriptome: analysis code, derived results and validation-cohort inputs

Analysis code, derived result tables, figures and validation-cohort inputs for a study of non-extensive (Tsallis) statistics in the glioblastoma transcriptome. Expression deviations of each sample are fitted with q-Gaussian laws by maximum likelihood. In a longitudinal GLASS cohort (230 libraries from 115 IDH-wildtype...

Designing a user-centered mHealth screening system for children in low-resource settings: A multi-stakeholder implementation study.

Scalable mHealth hearing-screening systems should prioritize simple, multimodal workflows, offline functionality, role-specific preparation, transparent decision support, and structured referral pathways.

Explainable AI model for predicting customer service communication effectiveness: A computational design science approach

The NMC Theory for Global Bipolarity: A Structural Law of The Atomic Era

By using an axiomatic method, this manuscript identifies the first structural law ever formulated in International Relations. It introduces a new ontology of global order and shows that the post-1945 system obeys a geometric constraint that permits only two true Poles. Appendices 1-3 focus on method which is new and he...

Searching for the truth? search engines and their AI affordances’ responses to conspiratorial search practices

Developed search query sets informed by conspiratorial and non-conspiratorial information-seeking practices of online forums are developed, using the chemtrails and 15-minute cities conspiracy theories as case studies.

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.