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Explainable Artificial Intelligence Second World Conference, xAI 2024, Valletta, Malta, July 17–19, 2024, Proceedings, Part IV /

This four-volume set constitutes the refereed proceedings of the Second World Conference on Explainable Artificial Intelligence, xAI 2024, held in Valletta, Malta, during July 17-19, 2024. The 95 full papers presented were carefully reviewed and selected from 204 submissions. The conference papers a...

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Korporativní autor: SpringerLink (Online service)
Další autoři: Longo, Luca (Editor), Lapuschkin, Sebastian (Editor), Seifert, Christin (Editor)
Médium: Elektronický zdroj E-kniha
Jazyk:angličtina
Vydáno: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Vydání:1st ed. 2024.
Edice:Communications in Computer and Information Science, 2156
Témata:
Artificial intelligence.
Natural language processing (Computer science).
Application software.
Computer networks .
Artificial Intelligence.
Natural Language Processing (NLP).
Computer and Information Systems Applications.
Computer Communication Networks.
On-line přístup:https://doi.org/10.1007/978-3-031-63803-9
Tagy: Přidat tag
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Obsah:
  • -- Explainable AI in healthcare and computational neuroscience.
  • SRFAMap: a method for mapping integrated gradients of a CNN trained with statistical radiomic features to medical image saliency maps.
  • Transparently Predicting Therapy Compliance of Young Adults Following Ischemic Stroke.
  • Precision medicine in student health: Insights from Tsetlin Machines into chronic pain and psychological distress.
  • Evaluating Local Explainable AI Techniques for the Classification of Chest X-ray Images.
  • Feature importance to explain multimodal prediction models. A clinical use case.
  • Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures.
  • Increasing Explainability in Time Series Classification by Functional Decomposition.
  • Towards Evaluation of Explainable Artificial Intelligence in Streaming Data.
  • Quantitative Evaluation of xAI Methods for Multivariate Time Series - A Case Study for a CNN-based MI Detection Model.
  • Explainable AI for improved human-computer interaction and Software Engineering for explainability.
  • Influenciae: A library for tracing the influence back to the data-points.
  • Explainability Engineering Challenges: Connecting Explainability Levels to Run-time Explainability.
  • On the Explainability of Financial Robo-advice Systems.
  • Can I trust my anomaly detection system? A case study based on explainable AI..
  • Explanations considered harmful: The Impact of misleading Explanations on Accuracy in hybrid human-AI decision making.
  • Human emotions in AI explanations.
  • Study on the Helpfulness of Explainable Artificial Intelligence.
  • Applications of explainable artificial intelligence.
  • Pricing Risk: An XAI Analysis of Irish Car Insurance Premiums.
  • Exploring the Role of Explainable AI in the Development and Qualification of Aircraft Quality Assurance Processes: A Case Study.
  • Explainable Artificial Intelligence applied to Predictive Maintenance: Comparison of Post-hoc Explainability Techniques.
  • A comparative analysis of SHAP, LIME, ANCHORS, and DICE for interpreting a dense neural network in Credit Card Fraud Detection.
  • Application of the representative measure approach to assess the reliability of decision trees in dealing with unseen vehicle collision data.
  • Ensuring Safe Social Navigation via Explainable Probabilistic and Conformal Safety Regions.
  • Explaining AI Decisions: Towards Achieving Human-Centered Explainability in Smart Home Environments.
  • AcME-AD: Accelerated Model Explanations for Anomaly Detection.

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