Artificial Intelligence Approaches for the Detection of Normal Pressure Hydrocephalus: A Systematic Review

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(7), P. 3653 - 3653

Published: March 26, 2025

Normal pressure hydrocephalus (NPH) is a neurological disorder characterized by altered cerebrospinal fluid accumulation in the brain’s ventricles, leading to symptoms such as gait disturbance and cognitive impairment. Artificial intelligence (AI), including machine learning (ML) deep (DL), shows promise diagnosing NPH using medical images. In this systematic review, we examined 21 papers on use of AI detecting NPH. The studies primarily focused differentiating from other neurodegenerative disorders, Parkinson’s disease Alzheimer’s disease. We found that traditional ML methods like Support Vector Machines, Random Forest, Logistic Regression were commonly used, while DL methods, particularly Deep Convolutional Neural Networks, also widely employed. accuracy these approaches varied, ranging 70% 95% conditions. Feature selection techniques used identify relevant parameters for diagnosis. MRI scans more frequently than CT scans, but both modalities showed promise. Evaluation metrics Dice similarity coefficients ROC-AUC most typical model performance. Challenges implementing clinical practice identified, authors suggested hybrid deep-traditional framework could enhance Further research needed maximize benefits addressing limitations.

Language: Английский

Intelligent identification of coal miners with fatty liver under a cascade reduction strategy

Engineering Analysis with Boundary Elements, Journal Year: 2025, Volume and Issue: 176, P. 106262 - 106262

Published: April 11, 2025

Language: Английский

Hybrid-Driven Risk Assessment Methodology for Coal and Gas Outburst: Integration of Complex Network, Disaster Mechanism, and Multi-Level Fusion Modeling

Process Safety and Environmental Protection, Journal Year: 2025, Volume and Issue: unknown, P. 107226 - 107226

Published: May 1, 2025

Language: Английский