Results 201 to 210 of about 36,209 (267)

Predicting early neurological deterioration in acute branch atheromatous disease without reperfusion therapy: a machine learning model. [PDF]

Front Neurosci
Zeng L, He W, Lu X, Zhang L.
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

Predicting major adverse cardiovascular and cerebrovascular events in chronic heart failure: a machine learning study. [PDF]

Ann Med
Feng S, Fan B, Bai J, Gu Y, Li Z, Lu L, Wang D.   +6 more
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

Toward transparent intelligence: Explainable stacked ensembles learning for LiDAR point cloud segmentation. [PDF]

PLoS One
Bondhon AR, Dey EK.
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

Quantifying and mapping uncertainty in urban sentiment prediction: a combined approach with entropy and SHAP explanations. [PDF]

Front Public Health
Betco I, Ribeiro AI, Viana CM, Rocha J.
europepmc   +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

Explainable machine learning identifies knee morphology thresholds for arthroscopic medial meniscus posterior root tear: a retrospective cohort study. [PDF]

Front Med (Lausanne)
Zhang M, Guo F, Li Y, Zheng J, Yu Y, Chen M, Li R, Liao Y, Chen Q, He C.   +9 more
europepmc   +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