Results 191 to 200 of about 31,305 (267)

Artificial intelligence–driven decoupling structure–activity relationship for lithium‐ion batteries

InfoScience, EarlyView.
Artificial intelligence can efferently accelerate the high‐throughput screening of battery materials, the analysis of multiphase mechanisms, and the precise prediction of capacity and cycle life. This review systematically summarizes the applications of machine learning (ML) in decoupling the complex structure‐activity relationships of lithium‐ion ...
Tao Wang, Yuhang Meng, Tianhao Chen, Xiangfen Jiang, Yoshio Bando, Jinjue Zeng, Xuebin Wang   +6 more
wiley   +1 more source

Untargeted metabolomics integrated with SHAP analysis identifies novel biomarkers of oxaliplatin induced peripheral neurotoxicity in gastric cancer. [PDF]

Transl Cancer Res
Hua Y, Liu X, Lv J, Zhang Y, Ding Y, Chen J.   +5 more
europepmc   +1 more source

Metrological and Algorithmic Traceability of Machine Learning in Laboratory Medicine

Journal of Clinical Laboratory Analysis, EarlyView.
Machine learning is increasingly used in clinical laboratory medicine for test interpretation, outcome prediction, and laboratory operations, but its safe implementation requires traceability that covers both measurement science and data‐driven computation.
Qing Li, Mario Plebani
wiley   +1 more source

Association of depressive symptoms with systemic immune-inflammation index and platelet parameters among survivors of myocardial infarction: a cross-sectional NHANES study enhanced by machine learning and SHAP analysis. [PDF]

BMC Psychiatry
Wang Z, Xu Q, Yu S, Sun J, Lv J, Huang Q, Huang C, Sun Y.   +7 more
europepmc   +1 more source

Artificial intelligence‐assisted nanozyme design for medical and environmental applications

Journal of Intelligent Medicine, EarlyView.
AI‐assisted nanozyme design integrates cross‐source data and machine learning to enable predictive structure‐activity relationships, accelerating intelligent diagnostics, precision therapeutics, and environmental surveillance. Abstract Nanozymes, a class of nanomaterials with intrinsic enzyme‐like catalytic activities, have emerged as promising ...
Xiaolin Guo, Hao Zhang, Zihan Zhao, Qingshan Liu, Jiayi Liu, Jiang Huang, Changlong Liu, Xiaoyu Mu   +7 more
wiley   +1 more source

Interpretable Quantification of Scene-Induced Driver Visual Load: Linking Eye-Tracking Behavior to Road Scene Features via SHAP Analysis. [PDF]

J Eye Mov Res
Ni J, Shao Y, Guo Y, Gu Y.
europepmc   +1 more source

Early prediction of acute kidney injury in traumatic and non‐traumatic rhabdomyolysis using an interpretable machine learning model: A multicenter study with external validation

Journal of Intelligent Medicine, EarlyView.
Abstract Acute kidney injury (AKI) is a common and severe complication of rhabdomyolysis (RM), and early risk stratification remains challenging because of its multifactorial and heterogeneous nature. We developed and externally validated an interpretable machine learning (ML) model for early prediction of AKI in RM across traumatic and non‐traumatic ...
Chunli Liu, Jie Shi, Fengjuan Wang, Liang Ma, Huangang Hu, Li Zhang, Jie Song, Heng Jin, Dingwei Yang, Xiaoqin Guo, Haojun Fan, Qi Lv   +11 more
wiley   +1 more source

Identification of Laminar Structure in the Yingxiongling Shale Oil Sediment in China with Random Forests and SHAP Analysis. [PDF]

ACS Omega
Zhang F, Liu X, Aldrich C, Deng S, Li G.
europepmc   +1 more source

AI‐Driven Risk Governance for SMEs: From Predictive Analytics to Strategic Competitiveness

Strategic Change, EarlyView.
ABSTRACT Small and medium‐sized enterprises (SMEs) remain highly exposed to financial distress due to limited resources, volatile markets, and governance constraints. Traditional risk management often lacks a strategic and anticipatory orientation, highlighting the need for risk governance frameworks that integrate forecasting and adaptability.
Davide Liberato lo Conte, Giuseppe Sancetta, Nicola Cucari, Octavio Escobar   +3 more
wiley   +1 more source

Enhanced and Interpretable Prediction of Multiple Cancer Types Using a Stacking Ensemble Approach with SHAP Analysis. [PDF]

Bioengineering (Basel)
Ganie SM, Dutta Pramanik PK, Zhao Z.
europepmc   +1 more source