Infectious Diseases and Therapy, Journal Year: 2025, Volume and Issue: unknown
Published: April 10, 2025
Language: Английский
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: Jan. 15, 2025
A dynamics informed neural networks (DINNs) incorporating the susceptible-exposed-infectious-recovered-vaccinated (SEIRV) model was developed to enhance understanding of temporal evolution infectious diseases. This work integrates differential equations with deep predict time-varying parameters in SEIRV model. Experimental results based on reported data from China between January 1, and December 2022, demonstrate that proposed method can accurately learn future states. Our hybrid SEIRV-DNNs also be applied other diseases such as influenza dengue, some modifications compartments accommodate related control measures. approach will facilitate improving predictive modeling optimizing public health intervention strategies.
Language: Английский
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Published: Jan. 1, 2025
Language: Английский
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Journal of Medical Internet Research, Journal Year: 2025, Volume and Issue: 27, P. e68198 - e68198
Published: Jan. 22, 2025
There is a critical need for community engagement in the process of adopting artificial intelligence (AI) technologies public health. Public health practitioners and researchers have historically innovated areas like vaccination sanitation but been slower emerging such as generative AI. However, with increasingly complex funding, programming, research requirements, field now faces pivotal moment to enhance its agility responsiveness evolving challenges. Participatory methods are key components many current programs research. The well positioned ensure part AI applied population issues. Without engagement, adoption these may exclude significant portions population, particularly those fewest resources, potential exacerbate inequities. Risks privacy perpetuation bias more likely be avoided if designed knowledge existing disparities, strategies improving equity. This viewpoint proposes multifaceted approach safer effective integration following call action: (1) include basics technology training professional development; (2) use co-design health; (3) introduce governance best practice mechanisms that can guide prevent or mitigate harms. These actions will support application varied domains through framework transparent, responsive, equitable this technology, augmenting work improve outcomes while minimizing risks unintended consequences.
Language: Английский
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International Journal of Environmental Research and Public Health, Journal Year: 2025, Volume and Issue: 22(2), P. 199 - 199
Published: Jan. 30, 2025
Background: Artificial intelligence (AI) is revolutionizing occupational health and safety (OHS) by addressing workplace hazards enhancing employee well-being. This review explores the broader context of increasing automation digitalization, focusing on role human–AI interaction in improving health, safety, productivity while considering associated challenges. Methods: A narrative methodology was employed, involving a comprehensive literature search PubMed, Embase, Scopus for studies published within last 25 years. After screening relevance eligibility, total 52 articles were included final analysis. These publications examined various AI applications OHS, such as wearable technologies, predictive analytics, ergonomic tools, with focus their contributions limitations. Results: Key findings demonstrate that enhances hazard detection, enables real-time monitoring, improves training through immersive simulations, significantly contributing to safer more efficient workplaces. However, challenges data privacy concerns, algorithmic biases, reduced worker autonomy identified significant barriers adoption OHS. Conclusions: holds great promise transforming OHS practices, but its integration requires ethical frameworks human-centric collaboration models ensure transparency, equity, empowerment. Addressing these will allow workplaces harness full potential creating safer, healthier, sustainable environments.
Language: Английский
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International Journal of Mathematical Engineering and Management Sciences, Journal Year: 2025, Volume and Issue: 10(2), P. 522 - 536
Published: Feb. 7, 2025
This research focuses on a combined simulation model for analyzing the spatial distribution of epidemics by combining global mixing assumption individuals with two-dimensional probabilistic cellular automata (CA). The presented in this paper is designed to simulate diseases spatially structured population. It incorporates stochastic compartment that uses regime, CA constructing decision support system controlling epidemics. positions elementary populations regular lattice, whereas applies sets persons who have same epidemic regime community. Previous models involved dynamic and are incorporated into most systems but more limited their representation geographic spread diseases. Alternatively, as individual can capture temporal pattern through local near-neighbor interactions. They consist rather separate cells one or multi-dimensional space, where each cell has constant number neighbors. Since predict some proper mathematical models, they potential improving prediction preventive measures public health management. results study show improvement quality response management numerical modeling studies using ensemble based random partition analysis.
Language: Английский
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Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 473 - 504
Published: Jan. 10, 2025
The utilization of the wearable devices (WDs) that are enhanced by artificial intelligence (AI) can have a notable potential in healthcare. This chapter aimed to provide an overview applications AI-driven WDs enhancing early detection and management virus infections. First, we presented examples highlight capabilities very monitoring infections such as COVID-19. In addition, provided on utility machine learning algorithms analyze large data for signs We also overviewed enable real-time surveillance effective outbreak management. showed how this be achieved via collection analysis diverse WDs' across various populations. Finally, discussed challenges ethical issues comes with virology diagnostics, including concerns about privacy security well issue equitable access.
Language: Английский
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Viruses, Journal Year: 2025, Volume and Issue: 17(3), P. 302 - 302
Published: Feb. 21, 2025
Equine influenza (EI) is a highly contagious respiratory disease caused by the equine virus (EIV), posing significant threat to populations worldwide. EIV exhibits considerable antigenic variability due its segmented genome, complicating long-term control efforts. Although infections are rarely fatal, EIV’s high transmissibility results in widespread outbreaks, leading substantial morbidity and economic impacts on veterinary care, quarantine, equestrian activities. The H3N8 subtype has undergone evolution, resulting emergence of distinct lineages, including Eurasian American, with Florida sublineage being particularly prevalent. Continuous genetic surveillance regular updates vaccine formulations necessary address drift maintain vaccination efficacy. Additionally, rare cross-species transmissions have raised concerns regarding zoonotic potential EIV. This review provides comprehensive overview epidemiology, pathogenesis, prevention EI, emphasizing strategies addressing socio-economic consequences regions where industry vital.
Language: Английский
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Journal of Fungi, Journal Year: 2025, Volume and Issue: 11(3), P. 207 - 207
Published: March 6, 2025
Sorghum (Sorghum bicolor L.) is a globally important energy and food crop that becoming increasingly integral to security the environment. However, its production significantly hampered by various fungal phytopathogens affect yield quality. This review aimed provide comprehensive overview of major affecting sorghum, their impact, current management strategies, potential future directions. The diseases covered include anthracnose, grain mold complex, charcoal rot, downy mildew, rust, with an emphasis on pathogenesis, symptomatology, overall economic, social, environmental impacts. From initial use fungicides shift biocontrol, rotation, intercropping, modern tactics breeding resistant cultivars against mentioned are discussed. In addition, this explores disease management, particular focus role technology, including digital agriculture, predictive modeling, remote sensing, IoT devices, in early warning, detection, management. It also key policy recommendations support farmers advance research thus emphasizing need for increased investment research, strengthening extension services, facilitating access necessary inputs, implementing effective regulatory policies. concluded although pose significant challenges, combined effort innovative policies can mitigate these issues, enhance resilience sorghum facilitate global issues.
Language: Английский
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Interdisciplinary Perspectives on Infectious Diseases, Journal Year: 2025, Volume and Issue: 2025(1)
Published: Jan. 1, 2025
This paper explores the transformative potential of integrating artificial intelligence (AI) in diagnosis and prognosis infectious diseases. By analyzing diverse datasets, including clinical symptoms, laboratory results, imaging data, AI algorithms can significantly enhance early detection personalized treatment strategies. reviews how AI-driven models improve diagnostic accuracy, predict patient outcomes, contribute to effective disease management. It also addresses challenges ethical considerations associated with AI, data privacy, algorithmic bias, equitable access healthcare. Highlighting case studies recent advancements, underscores AI's role revolutionizing management its implications for future healthcare delivery.
Language: Английский
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IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 167 - 196
Published: March 14, 2025
ML is a game-changing technology for improving diagnosis, customizing therapy, & streamlining healthcare delivery because of its capacity to handle learn from enormous volumes data. ML-based big data analysis has many benefits assimilating assessing vast intricate health care Early diagnosis monitoring drug-related safety issues were facilitated by algorithms that discovered hidden correlations between medications, medical products, adverse events. This chapter highlights the in Medicine. To achieve best possible results, it will be essential improve clinical decision support, sickness individualized treatment techniques. The discusses important keep mind when applying field, e.g., privacy, model interpretability, bias reduction, regulatory compliance. Lastly future medicine. Through responsible ethical adoption new technology, community can provide more individualized, efficient, effective patient outcomes.
Language: Английский
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