Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 189, P. 115738 - 115738
Published: Nov. 14, 2024
Language: Английский
Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 189, P. 115738 - 115738
Published: Nov. 14, 2024
Language: Английский
International Journal of Intelligent Systems, Journal Year: 2025, Volume and Issue: 2025(1)
Published: Jan. 1, 2025
We investigated the fusion of Intelligent Internet Medical Things (IIoMT) with depression management, aiming to autonomously identify, monitor, and offer accurate advice without direct professional intervention. Addressing pivotal questions regarding IIoMT’s role in identification, its correlation stress anxiety, impact machine learning (ML) deep (DL) on depressive disorders, challenges potential prospects integrating management IIoMT, this research offers significant contributions. It integrates artificial intelligence (AI) (IoT) paradigms expand studies, highlighting data science modeling’s practical application for intelligent service delivery real‐world settings, emphasizing benefits within IoT. Furthermore, it outlines an IIoMT architecture gathering, analyzing, preempting employing advanced analytics enhance intelligence. The study also identifies current challenges, future trajectories, solutions domain, contributing scientific understanding management. evaluates 168 closely related articles from various databases, including Web Science (WoS) Google Scholar, after rejection repeated books. shows that there is 48% growth articles, mainly focusing symptoms, detection, classification. Similarly, most being conducted United States America, trend increasing other countries around globe. These results suggest essence automated monitoring, suggestions handling depression.
Language: Английский
Citations
1Journal of Environmental Sciences, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 1, 2025
Language: Английский
Citations
0Cogent Psychology, Journal Year: 2025, Volume and Issue: 12(1)
Published: Feb. 4, 2025
Language: Английский
Citations
0Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: March 24, 2025
Higher education is essential because it exposes students to a variety of areas. The academic performance IT crucial and might fail if isn't documented identify the features influencing them, as well their strengths shortcomings. student prediction system needs be enhanced so that teachers can forecast students' performance. Numerous studies have been conducted increase accuracy students, but they encountered difficulties with unbalanced data algorithm tuning. To address these issues, study proposed different machine learning (ML) algorithms handled imbalanced by applying synthetic minority oversampling technique (SMOTE) employing hyperparameter tuning enhance during training process. ML models we used were decision tree (DT), k-nearest neighbor, XGBoost. fine-tuned Ant colony optimization (ACO) artificial bee techniques. Subsequently, techniques further models. After comparing results showed SMOTE ACO combined DT model outperformed other for prediction. Additionally, utilized Kendall Tau correlation coefficient analyze between factors positively or negatively impact success.
Language: Английский
Citations
0Brain Research Bulletin, Journal Year: 2024, Volume and Issue: unknown, P. 111104 - 111104
Published: Oct. 1, 2024
Language: Английский
Citations
2Brain and Behavior, Journal Year: 2024, Volume and Issue: 15(1)
Published: Dec. 31, 2024
Previous studies on neuroimaging findings in Alzheimer's disease (AD) patients with hallucinations and delusions have yielded inconsistent results. We aimed to systematically review of AD describe the most prominent features.
Language: Английский
Citations
1Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 189, P. 115738 - 115738
Published: Nov. 14, 2024
Language: Английский
Citations
0