„explainable artificial intelligence“
Suchergebnisse
759 Treffer
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Decoding pan-cancer treatment outcomes using multimodal real-world data and explainable artificial intelligence
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Toward transparent diagnosis of fatty liver disease: explainable AI-driven recommender systems using SHAP and LIME
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Transforming Alzheimer’s diagnosis: ADNet deep learning with explainable AI framework
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Zero-shot rise prompting framework and natural Language simplification for trustworthy explainable link prediction
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Fostering trust and interpretability in skin cancer classification: a hybrid framework of deep learning and machine learning with explainable AI
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Improving explainable AI interpretability with mathematical models for evaluating explanation methods
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Explainable biometrics: a systematic literature review
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Enhancing COVID-19 Diagnosis Accuracy and Transparency with Explainable Artificial Intelligence (XAI) Techniques
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Prediction of deoxynivalenol contamination in spring oats in Sweden using explainable artificial intelligence
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Explainable Artificial Intelligence in Alzheimer’s Disease Classification: A Systematic Review
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To be healed or to be hacked – Ethical issues and concerns about the use of VR and AI in mental health care
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Understanding oxidation of Fe-Cr-Al alloys through explainable artificial intelligence
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Shap-driven explainable AI with simulated annealing for optimized seizure detection using multichannel EEG signal
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Application of explainable artificial intelligence approach to predict student learning outcomes
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ADHD/CD-NET: automated EEG-based characterization of ADHD and CD using explainable deep neural network technique
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Automated heart disease prediction using improved explainable learning-based technique
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Explainable artificial intelligence (XAI) interactively working with humans as a junior cyber analyst
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Solving the Black Box Problem: A Normative Framework for Explainable Artificial Intelligence
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A novel approach using explainable prediction of default risk in peer-to-peer lending based on machine learning models
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Explainable deep learning techniques for wind speed forecasting in coastal areas: Integrating model configuration, regularization, early stopping, and SHAP analysis