Analysis of potential molecular targets and mechanisms of brominated flame retardants in causing osteoarthritis using network toxicology, machine learning, SHAP analysis, and molecular dynamics simulation. [PDF]
BMC Pharmacol ToxicolLiu Y, Shen G, Xia Z, Wang R, Dai Y.
europepmc +1 more source
Predicting 30-day survival after in-hospital cardiac arrest: a nationwide cohort study using machine learning and SHAP analysis. [PDF]
BMJ OpenGupta V +13 more
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Prediction and SHAP Analysis Integrating Morphological and Hemodynamic Parameters for Unruptured Intracranial Aneurysm Occlusion After Flow Diverter Treatment. [PDF]
CNS Neurosci TherZhang H +10 more
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Practical guide to SHAP analysis: Explaining supervised machine learning model predictions in drug development. [PDF]
Clin Transl SciPonce-Bobadilla AV +4 more
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A KAN-SHAP Framework for Fault Detection and Analysis in Smart Grids
2025 International Joint Conference on Neural Networks (IJCNN)Predictive maintenance is critical for ensuring the reliability and efficiency of Medium Voltage (MV) power grids. This paper presents a novel framework combining Kolmogorov– Arnold Networks (KANs) with SHapley Additive ex- Planations (SHAP) to predict and interpret real-world faults detected in Azienda Comunale Energia e Ambiente (ACEA)’s MV grid in ...
Enrico De Santis +2 more
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Dimensionality Reduction based on SHAP Analysis: A Simple and Trustworthy Approach
2020 International Conference on Communication and Signal Processing (ICCSP), 2020In this 21st century the world is driven by data, analysis, and predictions based on this data is substantial. However, these predictions that have an immense impact on our daily life comes with an overhead of complex data mining and large datasets. With this paper, we will suggest a way to reduce the dimensionality of the dataset without a great loss ...
Chejarla Santosh Kumar +4 more
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SHAP-Driven Feature Analysis Approach for Epileptic Seizure Prediction
Journal of Medical SystemsPredicting epileptic seizures presents a substantial difficulty in healthcare, with considerable implications for enhancing patient outcomes and quality of life. This paper presents an explainable artificial intelligence (AI) that integrates a one-dimensional convolutional neural network (1D-CNN) with SHapley Additive exPlanations (SHAP).
Mohsin Hasan +2 more
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SDGs India Index Analysis using SHAP
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Noise robustness analysis of Shapley value for Deep SHAP
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