Results 151 to 160 of about 5,693,469 (294)

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Data‐Efficient Cycle‐Level Capacity Prediction Using 1D Deep Convolutional Network

Advanced Intelligent Discovery, EarlyView.
We introduce DeepBat, a deep learning framework featuring a 1D convolutional backbone designed to extract latent degradation patterns from a microstructurally diverse electrode dataset. By learning complex formulation–performance relationships, the model accurately predicts long‐term specific discharge capacity using limited early‐cycle data, providing
Tao Huang, Bing Sun, Zhigang Chen, Chenyu Zhao, Eugene Bakker, Yaojie Lei, Lingfei Zhao, Shijian Wang, Chao Liu, Virginia Xiaojun He, Bahram Shirzadi, Hao Liu, Xin Xi, Ruiliu Liu, Dongqing Wu, Guodong Long, Guoxiu Wang   +16 more
wiley   +1 more source

A Decision Method for Benefit Distribution Mechanism of Shared End Distribution on Shapley Value.

Comput Intell Neurosci, 2022
Zhang H, Hou Y, He FF.
europepmc   +1 more source

Single NTU-value solutions [PDF]

We propose a variation of the Hart and Mas-Colell non-cooperative bargaining model for n-person games in coalitional form. This strategic game implements, in the limit, a new NTU-value for the class of monotonic games.
Emililo Calvo
core  

Current Standards of Monitoring Models in Healthcare Settings

Advanced Intelligent Discovery, EarlyView.
AI/ML‐enabled medical devices are entering clinical practice faster than monitoring standards mature. This review highlights gaps in postmarket surveillance, limited use of predetermined change‐control plans, and the need for ongoing performance tracking, drift detection, explainability, and workflow‐aware governance to support safer, more reliable ...
Alan Kay, Daljit Takher, Wenting Liu, Emily Wittrup, Gilbert S. Omenn, Kayvan Najarian   +5 more
wiley   +1 more source

MARGINAL CONTRIBUTIONS AND EXTERNALITIES IN THE VALUE [PDF]

For games in partition function form, we explore the implications of distinguishing between the concepts of intrinsic marginal contributions and externalities.
Roberto Serrano, Geoffroy de Clippel
core   +2 more sources

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

The Shapley value for a fair division of group discounts for coordinating cooling loads. [PDF]

PLoS One, 2020
Maleki S, Rahwan T, Ghosh S, Malibari A, Alghazzawi D, Rogers A, Beigy H, Jennings NR.   +7 more
europepmc   +1 more source

Shapley-like values for interval bankruptcy games [PDF]

In this paper interval bankruptcy games arising from bankruptcy situations with interval claims are introduced. For this class of cooperative games two (marginal-based) Shapley-like values are considered and the relation between them is studied.
Rodica Branzei, Stef Tijs, Dinko Dimitrov   +2 more
core  

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