Results 141 to 150 of about 2,644 (209)

Majorbio Cloud 2026 Update: An End‐to‐End Solution for Proteomics Research

iMetaMed, EarlyView.
The recent upgrade of Majorbio Cloud facilitates a more streamlined and accurate research process, aiding researchers across the various proteomics subfields. Furthermore, it propels the advancement of multi‐layered, multi‐omics scientific investigations centered around proteins.
Caiping Shi, Chang Han, Jichen Han, Bing Yang, Yachen Dong, Jianhua Zhao, Binxu Liu, Rundong Fang, Wenyao Fu, Jiawen Ma, Meng Luo, Lixing Feng, Yitong Feng, Huimin Cui, Mengxi Li, Huasheng Huang, Xianglin Zhang, Kegang Yu   +17 more
wiley   +1 more source

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

The Role of Admission Probabilities in the Deferred Acceptance Mechanism: An Experimental Study

International Studies of Economics, EarlyView.
ABSTRACT Although students theoretically need not consider admission probabilities under strategy‐proof mechanisms in school choice problems, our study reveals a significant correlation between students' applications and their beliefs about admission probabilities in the deferred acceptance mechanism.
Shuxian Hong, Yi Yang
wiley   +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

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

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

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

Exploration of a Multimodal Machine Learning Model Integrating Ultrasound and Clinical Indicators for the Diagnosis of Diabetic Peripheral Neuropathy

Journal of Ultrasound in Medicine, EarlyView.
Objectives Based on ultrasound technology and clinical indicators, this study intends to develop multiple risk prediction models for diabetic peripheral neuropathy (DPN), conduct comparative analyses of these models, and further evaluate and validate the diagnostic efficacy of the optimal model for DPN as well as its potential in clinical application ...
Bo‐yu She, Meng‐lu Song, Wen‐bin Chen, Kun‐bin Wu, Zhen‐han Lai   +4 more
wiley   +1 more source

Accuracy of Key Sonographic Markers for Juxta‐Articular Fractures

Journal of Ultrasound in Medicine, EarlyView.
Objectives To systematically evaluate sonographic features of long bone juxta‐articular fractures and identify key diagnostic predictors using machine learning‐based feature selection. Methods This prospective single‐center diagnostic accuracy study enrolled 121 patients with clinically suspected juxta‐articular fractures.
Xiaofang Fu, Lirong Liu, Hao Sun, Changqin Sun, Qinhan Yang, Mengjie Dou, Duo Shi, Junpu Hu, Zhiming He, Guangquan Zhou, Shiyu Jin, Faqin Lv   +11 more
wiley   +1 more source

The Role of Artificial Intelligence in Modern Allergology: A Review of Applications in Diagnosis, Prediction, and Management

JEADV Clinical Practice, EarlyView.
ABSTRACT Artificial Intelligence is rapidly transforming allergology by enhancing diagnosis, risk prediction, automation, patient communication, education, and therapy development. Machine learning approaches, including convolutional neural networks, recurrent architectures, and transformer‐based models, enable analysis of complex datasets from ...
Sebastian Seurig, Stephan Traidl, Sonja Mathes   +2 more
wiley   +1 more source