Explainable Deep Learning Approach for Multi-Class Brain Magnetic Resonance Imaging Tumor Classification and Localization Using Gradient-Weighted Class Activation Mapping by Tahir Hussain, Hayaru Shouno

Subjects: “…model explainability…”
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Deep learning-based detection and identification of brain tumor biomarkers in quantitative MR-images by Iulian Emil Tampu, Neda Haj-Hosseini, Ida Blystad, Anders Eklund

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Non-Differentiable Loss Function Optimization and Interaction Effect Discovery in Insurance Pricing Using the Genetic Algorithm by Robin Van Oirbeek, Félix Vandervorst, Thomas Bury, Gireg Willame, Christopher Grumiau, Tim Verdonck

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Toward User-Guided Seismic Facies Interpretation With a Pre-Trained Large Vision Model by Joshua Atolagbe, Ardiansyah Koeshidayatullah

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Enhancing Influenza Detection through Integrative Machine Learning and Nasopharyngeal Metabolomic Profiling: A Comprehensive Study by Md. Shaheenur Islam Sumon, Md Sakib Abrar Hossain, Haya Al-Sulaiti, Hadi M. Yassine, Muhammad E. H. Chowdhury

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Multilayer Concept Drift Detection Method Based on Model Explainability by Haolan Zhang, Xinyi Chen, Min Hu, Vijayan Sugumaran

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Explainable Connectionist-Temporal-Classification-Based Scene Text Recognition by Rina Buoy, Masakazu Iwamura, Sovila Srun, Koichi Kise

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Visual explanation method for reversible neural networks by Xinying MU, Bingbing SONG, Fanxiao LI, Yisen ZHENG, Wei ZHOU, Yunyun DONG

Subjects: “…model explainability…”
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Machine learning approaches for prediction of early death among lung cancer patients with bone metastases using routine clinical characteristics: An analysis of 19,887 patients by Yunpeng Cui, Xuedong Shi, Shengjie Wang, Yong Qin, Bailin Wang, Xiaotong Che, Mingxing Lei, Mingxing Lei, Mingxing Lei

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Interpretability Using Reconstruction of Capsule Networks by Vranay Dominik, Ruzmetov Mykhailo, Sinčák Peter

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Visual explanation method for reversible neural networks by Xinying MU, Bingbing SONG, Fanxiao LI, Yisen ZHENG, Wei ZHOU, Yunyun DONG

Subjects: “…model explainability…”
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Explainable Artificial Intelligence for Crowd Forecasting Using Global Ensemble Echo State Networks by Chamod Samarajeewa, Daswin De Silva, Milos Manic, Nishan Mills, Prabod Rathnayaka, Andrew Jennings

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A new method for exploring gene–gene and gene–environment interactions in GWAS with tree ensemble methods and SHAP values by Pål V. Johnsen, Signe Riemer-Sørensen, Andrew Thomas DeWan, Megan E. Cahill, Mette Langaas

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A systematic review on the integration of explainable artificial intelligence in intrusion detection systems to enhancing transparency and interpretability in cybersecurity by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

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Explainable Deep Learning: A Visual Analytics Approach with Transition Matrices by Pavlo Radiuk, Olexander Barmak, Eduard Manziuk, Iurii Krak

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Explainable Approaches for Forecasting Building Electricity Consumption by Nikos Sakkas, Sofia Yfanti, Pooja Shah, Nikitas Sakkas, Christina Chaniotakis, Costas Daskalakis, Eduard Barbu, Marharyta Domnich

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OVANet: Dual Attention Mechanism Based New Deep Learning Framework for Diagnosis and Classification of Ovarian Cancer Subtypes From Histopathological Images by Tahasin Ahmed Fahim, Fatema Binte Alam, Kazi Tanvir Ahmmed

Subjects: “…histopathological images model explainability using Grad-CAM…”
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Comparing ANOVA and PowerShap Feature Selection Methods via Shapley Additive Explanations of Models of Mental Workload Built with the Theta and Alpha EEG Band Ratios by Bujar Raufi, Luca Longo

Subjects: “…model explainability…”
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A Distinctive Explainable Machine Learning Framework for Detection of Polycystic Ovary Syndrome by Varada Vivek Khanna, Krishnaraj Chadaga, Niranajana Sampathila, Srikanth Prabhu, Venkatesh Bhandage, Govardhan K. Hegde

Subjects: “…local Interpretable model explainer…”
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