Results 131 to 140 of about 29,456 (261)

Prediction of hypertensive disorders of pregnancy in advanced-age pregnant women using SHAP value and XGBoost. [PDF]

Sci Rep
Wang J, Zhu H, Gu W.
europepmc   +1 more source

Multicenter Validation of Machine Learning Models for Predicting Myopia Progression Across School‐Based Screening and Optical Intervention Settings in Chinese Children and Adolescents

Advanced Intelligent Discovery, EarlyView.
Machine‐learning models predict myopia trajectories from 12 routine ocular variables in 40 445 children across 10 hospitals. Externally validated across school‐based screening and optical‐intervention settings, the best models achieve AUROC 0.97 for myopia status and R2 0.83 for spherical equivalent, enabling personalized risk stratification to curb ...
Yitong Zhang, Mingxuan Liu, Yifei Chen, Ying Wu, Lijun Zhang, Mengyao Guo, Yulan Yan, Runmei Wei, Zihan Cui, Peng Luo, Fang Chen, Bo Yang, Youcang Han, Xiaoyang Liu, Qiyuan Tian   +14 more
wiley   +1 more source

HYAL3 as a therapeutic target for pulmonary arterial Hypertension-Cardiomyopathy comorbidity: an integrative analysis combined with machine learning and SHAP value interpretation. [PDF]

Front Pharmacol
Hu J, Zhang W, Zeng Q, Yang M, Zhang L, Xu Y.   +5 more
europepmc   +1 more source

A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni, Md. Alif Sheakh, Mst. Sazia Tahosin, Md. Zahid Hasan, Taslima Ferdaus Shuva, Touhid Bhuiyan, Muhammad Ali Abdullah Almoyad, Nabil Anan Orka, Md. Tanvir Rahman, Risala Tasin Khan, M. Shamim Kaiser, Mohammad Ali Moni   +11 more
wiley   +1 more source

Machine learning-based screening model for Tic disorders comorbid with attention-deficit/hyperactivity disorder in children and SHAP value interpretation: a retrospective observational study. [PDF]

Sci Rep
Chen Z, Wang X, Chai Y, Hu Y, Jia R, Han F.   +5 more
europepmc   +1 more source

Interpretable Short‐Term Electric Load Forecasting

Advanced Intelligent Systems, EarlyView.
A temporal fusion transformer is implemented to generate day‐ahead forecasts of the hourly electrical load of a departmentbuilding at an Italian university. A forecasting performance improvement of more than 25% compared with established benchmark models and a provision of inherent robust interpretability insights reveal the potential of this model for
Alessandro Nicola, Giorgia Ghione, Vincenzo Randazzo, Vincenzo Franzitta, Marco Badami, Eros Pasero, Giansalvo Cirrincione   +6 more
wiley   +1 more source

Integrating Reinforcement Learning With Explainable Artificial Intelligence for Real‐Time Clinical Decision Support in Dynamic Healthcare Environments

Advanced Intelligent Systems, EarlyView.
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha, MD Faiaz Zaman Dehan, Kazi Md. Tanvir Anzum   +2 more
wiley   +1 more source

Machine Learning Based Early Diagnosis of ADHD with SHAP Value Interpretation: A Retrospective Observational Study. [PDF]

Neuropsychiatr Dis Treat
Zhang X, Xiao X, Luo Y, Xiao W, Cao Y, Chang Y, Wu D, Xu H, Zhao J, Deng X, Jiang Y, Xie R, Liu Y.   +12 more
europepmc   +1 more source

SHAP values through General Fourier Representations: Theory and Applications

This article establishes a rigorous spectral framework for the mathematical analysis of SHAP values. We show that any predictive model defined on a discrete or multi-valued input space admits a generalized Fourier expansion with respect to an orthonormalisation tensor-product basis constructed under a product probability measure.
openaire   +2 more sources

Comparative Analysis of Model‐Agnostic Explanation Methods in Materials Science

Advanced Intelligent Systems, EarlyView.
To address the critical lack of explainable artificial intelligence (XAI) benchmarks in materials science, we present a quantitative and qualitative analysis of six XAI methods applied to molecular fingerprints. Our results reveal significant discrepancies in feature importance rankings, demonstrating that the chosen explanation approach introduces ...
Anna Przybyłowska, Joanna Neubauer, Monika Sztuder, Witold Taisner, Agnieszka Hryniewicka, Julia Kolodziejczyk, Marta Eliza Plonska‐Brzezinska, Dariusz Brzezinski   +7 more
wiley   +1 more source