explainable ai

The Role of Explainability in AI for Industry

AI-Enabled Atrial Fibrillation Detection, Prediction, and Classification Based on ECG Data: A Review

This review systematically examines AI-based approaches for AF analysis, evaluating their advantages and limitations using key performance metrics, including accuracy, sensitivity, specificity, and F-score.

A decisive, untried test of the hybrid magnetite/radical-pair avian magnetic compass: protocol for Emlen-funnel trials under 0.05-10 mT static fields

Two mechanisms claim to explain the avian magnetic compass. The radical-pair model (cryptochrome-4 in the retina) predicts that compass information saturates as an applied static field grows from 0.05 to 10 mT. The newer hybrid model (Hore et al., PNAS 2026) adds a single-domain magnetite nanoparticle that amplifies th...

Enterprise AI Architecture Governance and Risk Framework

A comprehensive governance framework built upon SAP Enterprise Architecture Framework is proposed that enables organizations to build secure, scalable, transparent, explainable, compliant, resilient, and trustworthy AI ecosystems that accelerate innovation while minimizing enterprise risk and supporting long-term digit...

AI and Islamic Finance

Artificial intelligence is reshaping financial analysis, institutional decision-making and service provision, however the evolution of its uses in Islamic finance is still not sufficiently consolidated. The study examines the publication trends, main contributors and conceptual structure of AI research in Islamic finan...

Artificial intelligence is transforming disease surveillance, but governance is failing to keep pace

Artificial intelligence (AI) is transforming disease surveillance by enabling early outbreak detection, predictive modeling, and real-time analysis of diverse health data sources. These advances can strengthen epidemic preparedness and improve public health decision-making. However, AI adoption has progressed faster th...

Advanced Explainable AI Modeling for Structural Response Prediction of Reinforced Concrete Beams

This study presents a novel hybrid machine learning framework for predicting the structural behavior of reinforced concrete (RC) beams based on a comprehensive international database. The dataset, compiled from 73 references between 1955 and 2023, includes 33 input variables that describe the geometry, material propert...

Artificial Intelligence and the Future of Justice: Should AI Prosecute Criminals and Administer the Law?

This paper looks at the growing use of artificial intelligence (AI) in legal systems and asks whether AI should be given the power to prosecute criminals and manage law and order in a country. It looks at how AI is already used in courts and police work today, and explains the benefits, like speed and consistency. It a...

From Universality to Consciousness: Beyond the Skull, Into the World

AbstractThe laws of the world are common, but the world does not appear in the same manner to everybearer. This paper explains that difference without treating it as an exception to universal law. Its proposal is that a history of relations with the world folds back into the present as a condition of further formation....

Algorithmic auditing of AI credit scoring: integrating IFRS 9 model governance with ethical AI assessment

A multidimensional framework that integrates predictive performance, algorithmic fairness and explainability for the auditing of AI-based credit scoring models and provides auditors and regulators with a structured approach to assessing the performance, fairness and explainability of AI models in accordance with model...

Development and evaluation of a deep learning framework for screening of cervical lymph node metastasis in microscopic images of oral squamous cell carcinoma: A proof of concept study.

The developed framework is intended as a decision-support tool for pathologist support and screening and prioritisation of suspicious microscopic images and not as a replacement for slide-level diagnosis or immunohistochemistry.

Медиаобраз искусственного интеллекта в массовом политическом воображении: между «умным государством» и «цифровым Левиафаном»

The article examines the media image of artificial intelligence as a significant element of the mass political imagination in the digital age. Its aim is to provide a political-science interpretation of the discursive frames through which AI becomes an object of public legitimation or criticism in the context of transf...