explainable ai

A comprehensive deep learning framework for colorectal cancer detection and classification using TECNN-MNGO model with explainable AI integration

Explainable AI for drug-resistant tuberculosis detection from chest X-rays: Multi-level interpretability and cross-dataset transfer learning

Explainable AI-based prediction of lithium-ion battery aging: A comparative study at low and moderate temperatures

Towards trustworthy and explainable AI for ocular disease diagnosis using an ontology-guided neuro-symbolic framework

Inside the black box: A comprehensive survey of explainable AI benchmarks, protocols, technical analysis, and open gaps

Artificial Intelligence for Real-Time Cyber Threat Classification and Emerging Threat Detection: A Structured Review of Methods, Datasets, Challenges, and Research Directions

The reviewed literature indicates that AI-based methodologies often demonstrate superior detection capabilities for intricate and previously unseen attack patterns compared to traditional methods; however, direct performance comparisons are complicated due to discrepancies in datasets, experimental designs, and evaluat...

An explainable generative AI framework for detecting low-rate API-based DDoS attacks in cloud environments

Adaptive Repayment Optimisation for SME Lending: A Stochastic Programming Framework with Generative AI Explanation

The Adaptive Repayment Optimisation Engine is introduced, a novel framework that applies constrained stochastic optimisation to the design of loan repayment schedules for small and medium-sized enterprises (SMEs) and contributes to the operations research literature by bridging stochastic programming, explainable AI, a...