XAI-Enhanced Machine Learning for Obesity Risk Classification: A Stacking Approach With LIME Explanations by Mohammad Azad, Md Faraz Kabir Khan, Sameh Abd El-Ghany

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Explainable AI for Healthcare 5.0: Opportunities and Challenges by Deepti Saraswat, Pronaya Bhattacharya, Ashwin Verma, Vivek Kumar Prasad, Sudeep Tanwar, Gulshan Sharma, Pitshou N. Bokoro, Ravi Sharma

Subjects: “…Explainable AI…”
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An LSTM approach to deciphering irrigation operations from remote sensing and groundwater levels records by Shiqi Wei, Tianfang Xu

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Global-Mapping-Consistency-Constrained Visual-Semantic Embedding for Interpreting Autonomous Perception Models by Chi Zhang, Meng Yuan, Xiaoning Ma, Ping Wei, Yuanqi Su, Li Li, Yuehu Liu

Subjects: “…Explainable AI evaluation…”
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Advancing Model Explainability: Visual Concept Knowledge Distillation for Concept Bottleneck Models by Ju-Hwan Lee, Dang Thanh Vu, Nam-Kyung Lee, Il-Hong Shin, Jin-Young Kim

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A latent diffusion approach to visual attribution in medical imaging by Ammar Adeel Siddiqui, Santosh Tirunagari, Tehseen Zia, David Windridge

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A Study on the Application of Explainable AI on Ensemble Models for Predictive Analysis of Chronic Kidney Disease by K. M. Tawsik Jawad, Anusha Verma, Fathi Amsaad, Lamia Ashraf

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Evaluating Explainable AI Methods in Deep Learning Models for Early Detection of Cerebral Palsy by Kimji N. Pellano, Inga Strumke, Daniel Groos, Lars Adde, Espen F. Alexander Ihlen

Subjects: “…Explainable AI…”
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PD_EBM: An Integrated Boosting Approach Based on Selective Features for Unveiling Parkinson's Disease Diagnosis With Global and Local Explanations by Fahmida Khanom, Mohammad Shorif Uddin, Rafid Mostafiz

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CIME4R: Exploring iterative, AI-guided chemical reaction optimization campaigns in their parameter space by Christina Humer, Rachel Nicholls, Henry Heberle, Moritz Heckmann, Michael Pühringer, Thomas Wolf, Maximilian Lübbesmeyer, Julian Heinrich, Julius Hillenbrand, Giulio Volpin, Marc Streit

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3MT Competition (EUSIPCO2024): A peek into the black box: Insights into the functionality of complex-valued neural networks for multichannel speech enhancement by Annika Briegleb

Subjects: “…Explainable AI…”
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Enhancing misogyny detection in bilingual texts using explainable AI and multilingual fine-tuned transformers by Ehtesham Hashmi, Sule Yildirim Yayilgan, Muhammad Mudassar Yamin, Mohib Ullah

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Clinical validation of explainable AI for fetal growth scans through multi-level, cross-institutional prospective end-user evaluation by Zahra Bashir, Manxi Lin, Aasa Feragen, Kamil Mikolaj, Caroline Taksøe-Vester, Anders Nymark Christensen, Morten B. S. Svendsen, Mette Hvilshøj Fabricius, Lisbeth Andreasen, Mads Nielsen, Martin Grønnebæk Tolsgaard

Subjects: “…Artificial intelligence, Fetal growth scans, Explainable AI, Human-AI collaboration…”
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Advanced sleep disorder detection using multi-layered ensemble learning and advanced data balancing techniques by Muhammad Mostafa Monowar, S. M. Nuruzzaman Nobel, Maharin Afroj, Md Abdul Hamid, Md Zia Uddin, Md Mohsin Kabir, M. F. Mridha

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Feature Selection in Cancer Classification: Utilizing Explainable Artificial Intelligence to Uncover Influential Genes in Machine Learning Models by Matheus Dalmolin, Karolayne S. Azevedo, Luísa C. de Souza, Caroline B. de Farias, Martina Lichtenfels, Marcelo A. C. Fernandes

Subjects: “…explainable AI…”
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Explainable AI-based suicidal and non-suicidal ideations detection from social media text with enhanced ensemble technique by Daniyal Alghazzawi, Hayat Ullah, Naila Tabassum, Sahar K. Badri, Muhammad Zubair Asghar

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Chinese Chat Room: AI Hallucinations, Epistemology and Cognition by Šekrst Kristina

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Deep learning-driven defense strategies for mitigating DDoS attacks in cloud computing environments by Doaa Mohsin Abd Ali Afraji, Jaime Lloret, Lourdes Peñalver

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SmartSkin-XAI: An Interpretable Deep Learning Approach for Enhanced Skin Cancer Diagnosis in Smart Healthcare by Sultanul Arifeen Hamim, Mubasshar U. I. Tamim, M. F. Mridha, Mejdl Safran, Dunren Che

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Retrospectively understanding the multifaceted interplay of COVID-19 outbreak, air pollution, and sociodemographic factors through explainable AI by Mohmmed Talib, Kripabandhu Ghosh, Gopala Krishna Darbha

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