explainable ai

Trustworthy and explainable artificial intelligence for reliability in advanced manufacturing: a critical review with applications in semiconductor packaging

Unit 1 AI and Its Subfields PPT

Unit I – AI and Its Subfields is an Open Educational Resource (OER) presentation developed for the AI Fundamentals course for undergraduate students. This presentation provides a structured introduction to Artificial Intelligence and its major concepts. It covers the definition, objectives, characteristics, history and...

Integrating Artificial Intelligence into Digital Transformation Strategy: A Framework for Sustainable Enterprise Growth

Digital transformation and artificial intelligence are reshaping how organizations develop capabilities, make decisions, innovate, and pursue sustainable performance. However, existing research largely examines digital transformation, Dynamic Capabilities, AI capability, organizational intelligence, and sustainability...

A tiered deep learning and symbolic reasoning framework for safe, explainable disease diagnosis

This study introduces a modular, AI-powered disease diagnosis system that combines deep learning, neuro-symbolic reasoning, and structured automation to support early, scalable, and explainable clinical decision-making. Built upon the large-scale DDXPlus dataset, the system processes over one million patient records in...

AnExplainable AI Engineering Framework for Claims-Only First-Stage Provider Audit Triage Using SHAP-Guided Hybrid Retrieval-Augmented Generation

This study proposes an explainable artificial intelligence (XAI) engineering workflow for provider-level healthcare claim audit prioritization using SHAP-guided hybrid retrieval-augmented generation (RAG). The framework integrates provider-level claim aggregation, tree-based risk screening, SHAP explanation, explorator...

AI Fundamentals – Unit II: Applications of Artificial Intelligence

Unit II – Applications of Artificial Intelligence is an Open Educational Resource (OER) presentation developed for the undergraduate AI Fundamentals course. This presentation introduces the applications of Artificial Intelligence across six important domains: Healthcare, Finance, Retail, Agriculture, Education, and Tra...

Trustworthy AI for Dengue Outbreak Forecasting Using a Temporal Fusion Transformer with Explainability and Uncertainty Estimation

The Usual Explanation of the Brazil-Nut Effect Fails on the Size of the Gap ── The gap between three 20 mm spheres admits only 3.0940 mm ── For "small grains fall through the gaps" to work, the diameter ratio must be at least 6.4641, while the effect is seen at about 4 ── It is the explanation that fails, on geometry ── [Paper 365]

Shake a mixture and the large grains come to the top. This paper asks whether the usual explanation survives the geometry──the answer is that it does not: the gap is too small. No new mathematical theorem and no new law is claimed. Scope of this paper (scope note): No new mathematical theorem and no new law is claimed─...

AI -Augmented HRM: transforming talent acquisition and employee experience in 2026.

Artificial Intelligence (AI) is becoming increasingly usual in HR management, especially in talent acquisition and AI-assisted decision making. But, in addition to the technological capacities, the successful application of AI needs HR professionals to understand and evaluate the recommendations of AI. In the present r...

Policing the Dark Web in the AI Era

The fast growth of dark web processes has made cybercrime an adaptive and intelligence-driven phenomenon that warrants a change in thinking about digital policing, traditionally basing it on fixed rules and post hoc investigation. The strategy involves integrating transformer-based semantic analysis, time behavior and...

Code for: Deep Learning for Odontoid Fractures: The Critical Role of Patient-Level Partitioning and Grad-CAM Verification in Model Generalization

Description This repository contains the complete, reproducible PyTorch source code for the study "Deep Learning for Odontoid Fractures: The Critical Role of Patient-Level Partitioning and Grad-CAM Verification in Model Generalization". The codebase implements an end-to-end deep learning framework designed to eliminate...

Beyond Traditional Engineering: How BIM Is Reshaping Engineering

This conceptual working paper introduces the Integrated BIM-to-Decision Framework, a six-layer architecture that connects the origin of information demand to accountable engineering decisions and closes the process through structured feedback. It addresses a persistent limitation in BIM implementation: the tendency to...