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Exploring Evaluation Methods for Interpretable Machine Learning: A Survey
Information, 2023 In recent times, the progress of machine learning has facilitated the development of decision support systems that exhibit predictive accuracy, surpassing human capabilities in certain scenarios.
Nourah Alangari +3 more
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Frontiers in Artificial Intelligence, 2022 The influence of Artificial Intelligence is growing, as is the need to make it as explainable as possible. Explainability is one of the main obstacles that AI faces today on the way to more practical implementation.
Jurgita Černevičienė +1 more
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A New Interpretable Unsupervised Anomaly Detection Method Based on Residual Explanation
IEEE Access, 2022 Despite the superior performance in modeling complex patterns to address challenging problems, the black-box nature of Deep Learning (DL) methods impose limitations to their application in real-world critical domains.
David F. N. Oliveira +8 more
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Frontiers in Artificial Intelligence, 2021 Cohort-independent robust mortality prediction model in patients with COVID-19 infection is not yet established. To build up a reliable, interpretable mortality prediction model with strong foresight, we have performed an international, bi-institutional ...
Tao Bai +17 more
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Identification of Epileptic EEG Signals Through TSK Transfer Learning Fuzzy System
Frontiers in Neuroscience, 2021 We propose a new model to identify epilepsy EEG signals. Some existing intelligent recognition technologies require that the training set and test set have the same distribution when recognizing EEG signals, some only consider reducing the marginal ...
Zhaoliang Zheng +5 more
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Abstracting Fairness: Oracles, Metrics, and Interpretability [PDF]
, 2020 It is well understood that classification algorithms, for example, for deciding on loan applications, cannot be evaluated for fairness without taking context into account.
Dwork, Cynthia +3 more
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M@n@gement, 2022 Data we collect and use in organisation and management studies look like ‘cold cases’. We want to offer more conversations, interpretations, arguments and even disputes. The ‘Interpreters’ is a nexus where academics invite colleagues and friends to analyse and discuss freely an argument, raw data, cases and qualitative materials.
Pomiès, Anissa +3 more
openaire +4 more sources
Explainable AI: A review of applications to neuroimaging data
Frontiers in Neuroscience, 2022 Deep neural networks (DNNs) have transformed the field of computer vision and currently constitute some of the best models for representations learned via hierarchical processing in the human brain. In medical imaging, these models have shown human-level
Farzad V. Farahani +6 more
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Frontiers in Physiology, 2023 Background: Radiofrequency catheter ablation (RFCA) therapy is the first-line treatment for atrial fibrillation (AF), the most common type of cardiac arrhythmia globally.
Shaheim Ogbomo-Harmitt +5 more
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Double Prior Network for Multidegradation Remote Sensing Image Super-Resolution
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Image super-resolution (SR) is widely used in remote sensing because it can effectively increase image details. Neural networks have shown remarkable performance in recent years, benefitting from their end-to-end training.
Mengyang Shi +3 more
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