explainable-ai

Documents about explainable-ai

• LRP-Based path relevances for global explanation of deep architectures#948422Repositorio de Universidad Autónoma de Chile.
• Explainable AI for cybersecurity automation, intelligence and trustworthiness in digital twin: Methods, taxonomy, challenges and prospects#976535OpenAlex
• Bioinspired hybrid optimisation and deep belief neural networks for early chronic kidney disease detection: an explainable clinical AI framework.#9696PubMed
• DeepDect: an explainable AI platform for face swapping and face generation DeepFake detection#161429Springer Nature OA
• Mitigating the Information Cocoon Effect in Cognitively Aligned Recommendations: A Human-Centered Approach#177645Digital Commons @ Michigan Tech
• Explainable AI for Intrusion Detection Systems: LIME and SHAP Applicability on Multi-Layer Perceptron#200919OpenAlex
• Metaverse in Healthcare Integrated with Explainable AI and Blockchain: Enabling Immersiveness, Ensuring Trust, and Providing Patient Data Security#200925OpenAlex
• An Explainable Generative AI Framework for Multi-Criteria Employee Churn Analysis#299177Springer Nature OA
• Artificial Intelligence to Help Reduce Delays and Bottlenecks in the Care Pathways for Rare Diseases: An Integrated Practitioner–Patient Approach#246869HAL (France)
• Can surgeons trust AI? Perspectives on machine learning in surgery and the importance of eXplainable Artificial Intelligence (XAI)#265693OpenAlex
• Machine Learning-Driven Prediction and Mechanistic Insight into CO <b><sub>2</sub></b> Adsorption on Biomass-Derived Activated Carbons Using Explainable AI (XAI)#311575Europe PMC
• Explainable AI (xAI) for Landslide Susceptibility Modeling: A Comparative Analysis of Machine Learning and Deep Learning Approaches#443646Springer Nature OA
• X-NET: explainable AI-based network data security framework for Healthcare 4.0#462358RUcore, Rutgers University Community Repository
• Privacy-preserving intrusion detection in IoT smart homes using a federated hybrid 1D-CNN–LSTM model with explainable AI#637748Springer Nature OA
• Machine learning prediction of threshold switching voltages indicates a filamentary-to-homogeneous transition in TiO2/TiO2-x/TiO2 memristors#269705Recep Tayyip Erdoğan University Institutional Repository
• Trustworthy hybrid model with dual dilated attention and BiConvLSTM for multi-horizon load forecasting#374343HAL (France)
• Robust and Interpretable Crop Recommendation: A Case Study on a Balanced Multi-crop Agronomic Dataset#424770HAL (France)
• Adaptive model poisoning detection in federated learning for EV charging networks: a blockchain-anchored explainable AI approach#1020725Springer Nature OA
• An Explainable Tiny-Fast Kolmogorov-Arnold Network for Gesture-Based Air Handwriting Recognition of Tifinagh Letters in Resource-Constrained IoT Device#382000DR-NTU (Digital Repository of NTU)
• Enhancing botnet attack detection using a hybrid deep learning model combining network flow and DNS query features with explainable AI for cybersecurity#443660Springer Nature OA
• Considering the inter-judge variability in the perceptual evaluation of speech and voice disorders and its integration into an automatic decision support system.#370846HAL (France)
• Методи оцінювання невизначеності прогнозів у системах підтримки прийняття рішень на основі моделей машинного навчання / Uncertainty Estimation Methods for Machine Learning Predictions in Decision Support Systems#656705Zenodo (CERN)
• Enhancing chronic disease management: hybrid graph networks and explainable AI for intelligent diagnosis#430064Figshare
• Оцінювання невизначеності та пояснюваності прогнозів у системах підтримки прийняття рішень на основі машинного навчання / Evaluating Prediction Uncertainty and Explainability in Machine Learning-Based Decision Support Systems#977882Zenodo (CERN)
• MaxGRNet: A Multi-Axis Vision Transformer with Improved Generalization for Eye Disease Classification Using Explainable AI with Insertion-Deletion Operations on Fundus Images#190276ODU Digital Commons
• Too Much Detail Kills the Vibe: Quantifying Lyrical Realism and Pop Music Virality#976900OSF
• Too Much Detail Kills the Vibe: Quantifying Lyrical Realism and Pop Music Virality#680769SocArXiv
• Explainable AI in Space : Second International Workshop, EASi 2026, Held in Conjunction with the 35th International Joint Conference on Artificial Intelligence, IJCAI-ECAI 2026, Bremen, Germany, August 15–21, 2026, Proceedings / edited by Jakub Nalepa, Przemysław Biecek, Krzysztof Kotowski, Lukasz Tulczyjew, Marek Kraft, Nicolas Longépé, Evridiki V. Ntagiou, Agata M. Wijata#487183Deutsche Nationalbibliothek
• QSSI 2026™: Quantum Sovereign Security Index — Definitive Master Release v10.0.0#282443Zenodo (CERN)