explainable ai

A Comprehensive Study of Machine Learning and Deep Learning for Heart Disease Prediction

The problems of this paper are the problems of this paper, and some future directions for constructing a reliable cardiac disease prediction system with clinical applications are proposed.

Machine Intuition

Can an artificial intelligence system select the right action before it can articulate a valid reason for that action? Addressing this question at the intersection of reasoning, interpretability, agent safety, and latent computation, we develop a non-anthropomorphic definition of machine intuition as pre-explanatory co...

Opening the Black Box a Crack: A Historical Development Review of Explainability and Interpretability of Black-Box Models

This article presents a narrative review of Explainability and Interpretability of Black-Box Models in the context of Artificial Intelligence. The literature on this topic has expanded substantially over recent decades, yet it remains fragmented across subfields, methods, and national research traditions. Drawing on an...

Opening the Black Box a Crack: A Historical Development Review of Explainability and Interpretability of Black-Box Models

This article presents a narrative review of Explainability and Interpretability of Black-Box Models in the context of Artificial Intelligence. The literature on this topic has expanded substantially over recent decades, yet it remains fragmented across subfields, methods, and national research traditions. Drawing on an...

Machine Intuition

Can an artificial intelligence system select the right action before it can articulate a valid reason for that action? Addressing this question at the intersection of reasoning, interpretability, agent safety, and latent computation, we develop a non-anthropomorphic definition of machine intuition as pre-explanatory co...

PATTERN-X: Guiding sustainable innovation in intelligent lighting systems through an explainable AI framework for technology convergence forecasting

A Systematic Literature Review of Emerging Big Data Analytics Using Hadoop: Applications, Trends, and Implications for Sustainability

The rapid expansion of Big Data has transformed data-driven decision-making across diverse sectors, including healthcare, cybersecurity, smart cities, and the Internet of Things (IoT). However, traditional data management platforms struggle to address the increasing volume, velocity, variety, and veracity of modern dat...

The Digital Transformation of Rehabilitation Medicine: A Narrative Review of Artificial Intelligence Innovations, Clinical Integration, and Future Paradigms.

BACKGROUND Traditional rehabilitation medicine, primarily dependent on qualitative clinical assessment and static therapeutic protocols, faces significant challenges in scalability, objectivity, and dynamic adaptability. The integration of Artificial Intelligence (AI) is catalyzing a paradigm shift from "experience-dri...

SPIRAL - A Cognitive Architecture for Artificial Intelligence

Spiral is a new theoretical framework for understanding how artificial intelligence can reason, design, and operate inside structured domains. The work presented in this manuscript introduces a cognitive geometry — a way of describing how an intelligent system moves through a space of constraints, possibilities, and la...

Blindness and epistemic injustice: a critical autoethnography of digital disablement in Thailand

Thailand’s digital transformation is presented as a route to inclusion, yet everyday accessibility remains unresolved for many disabled people. Combining policy document analysis with critical autoethnography, grounded in emancipatory disability research and analysed through a narrative approach, this article examines...

Artificial intelligence in healthcare: Technical advances, clinical integration, and future perspectives

This narrative review examines the evolution of artificial intelligence (AI) in healthcare, with a focus on the transition from early rule-based systems to modern deep learning architectures and their integration into clinical practice. We examine foundational technologies, including convolutional neural networks for i...

Algorithmic Publicity and the Right to a Fair Trial

Building on developments in the UK, EU, US, China and Estonia, it proposes doctrinal and procedural refinements, narrowly targeted platform duties and court-supervised AI monitoring tools to preserve jury trial and open justice while maintaining credible fair-trial guarantees in an algorithmic information environment.