Infectious Diseases and Therapy, Journal Year: 2025, Volume and Issue: unknown
Published: April 10, 2025
Language: Английский
International Medical Science Research Journal, Journal Year: 2024, Volume and Issue: 4(6), P. 647 - 667
Published: June 6, 2024
The integration of artificial intelligence (AI) and mobile health data has ushered in a new era real-time infectious disease surveillance, offering unprecedented insights into dynamics enabling proactive public interventions. This paper explores the innovative applications AI transforming traditional surveillance systems for diseases. By harnessing power algorithms, coupled with vast amount generated from devices, researchers authorities can now monitor outbreaks greater accuracy efficiency. AI-driven predictive models analyze diverse datasets, including demographic information, travel patterns, social media activity, to detect early signs emergence predict potential outbreaks. use provides wealth information that was previously inaccessible methods. Mobile apps, wearables, other connected devices enable continuous monitoring individuals' indicators, allowing detection symptoms rapid response threats. Furthermore, geolocation facilitates tracking population movements identification high-risk areas transmission. However, this approach also presents challenges ethical considerations. Privacy concerns regarding collection must be carefully addressed ensure rights are protected. Additionally, issues related quality, interoperability, algorithm bias need mitigated reliability effectiveness systems. In conclusion, holds immense promise revolutionizing surveillance. leveraging these technologies, gain valuable dynamics, enhance capabilities, implement targeted interventions prevent spread it is essential address considerations associated its responsible effective implementation. Keywords: Innovations, Real-Time Infectious Disease, Surveillance, AI, Data.
Language: Английский
Citations
16
Tropical Diseases Travel Medicine and Vaccines, Journal Year: 2025, Volume and Issue: 11(1)
Published: Jan. 2, 2025
Oropouche fever is an increasingly significant health concern in tropical and subtropical areas of South Central America, primarily spread by midge vectors. The virus (OROV) was first identified 1955 has been responsible for numerous outbreaks, particularly urban environments. Despite its prevalence, the disease often under-reported, making it difficult to fully understand impact. OROV typically causes febrile illness characterized symptoms such as headaches, muscle pain, and, occasionally, neurological issues meningitis. ability thrive both forested raised concerns regarding potential new regions, context climate change. This paper delves into epidemiology, clinical features, transmission patterns OROV, shedding light on difficulties diagnosing managing disease. absence specific treatments vaccines highlights urgent need continued research development targeted public strategies. Advancements molecular diagnostics vector control strategies can mitigate fever's However, a comprehensive approach involving increased surveillance, education, cross-border collaboration needed, especially global crisis may expand habitats, posing risks previously unaffected regions.
Language: Английский
Citations
3
Annals of Medicine, Journal Year: 2024, Volume and Issue: 56(1)
Published: June 10, 2024
Infectious diseases are a major threat for human and animal health worldwide. Artificial Intelligence (AI) combined algorithms including Machine Learning Big Data analytics have emerged as potential solution to analyse diverse datasets face challenges posed by infectious diseases. In this commentary we explore the applications limitations of ML management disease. It explores in key areas such outbreak prediction, pathogen identification, drug discovery, personalized medicine. We propose solutions mitigate these hurdles identify biomolecules effective treatment prevention addition use diseases, based on catastrophic evolution events identification biomolecular targets reduce risks vaccinomics discovery characterization vaccine protective antigens using intelligent techniques. These considerations set foundation developing strategies managing future.
Language: Английский
Citations
13
Horticulturae, Journal Year: 2025, Volume and Issue: 11(1), P. 46 - 46
Published: Jan. 6, 2025
Olive leaf spot (OLS), caused by Fusicladium oleagineum, is a significant disease affecting olive orchards, leading to reduced yields and compromising tree health. Early accurate detection of this critical for effective management. This study presents comprehensive assessment OLS progression in orchards integrating agronomic measurements multispectral imaging techniques. Key parameters—incidence, severity, diseased area, index—were systematically monitored from March October, revealing peak values 45% incidence April 35% severity May. Multispectral drone imagery, using sensors NIR, Red, Green, Red Edge spectral bands, enabled the calculation vegetation indices. Indices incorporating near-infrared such as SR705-750, exhibited strongest correlations with (correlation coefficients 0.72 0.68, respectively). combined approach highlights potential remote sensing early supports precision agriculture practices facilitating targeted interventions optimized orchard The findings underscore effectiveness traditional advanced analysis improve surveillance promote sustainable cultivation.
Language: Английский
Citations
1
Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 143, P. 109985 - 109985
Published: Jan. 13, 2025
Language: Английский
Citations
1
Case Studies in Chemical and Environmental Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 101106 - 101106
Published: Jan. 1, 2025
Language: Английский
Citations
1
Journal of Energy Storage, Journal Year: 2024, Volume and Issue: 99, P. 112835 - 112835
Published: Aug. 10, 2024
Language: Английский
Citations
6
Current Sexual Health Reports, Journal Year: 2024, Volume and Issue: 17(1)
Published: Dec. 4, 2024
Language: Английский
Citations
4
Cureus, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 7, 2025
Artificial intelligence (AI) has emerged as a transformative tool in the management of pandemics, significantly enhancing disease prediction, diagnostics, drug discovery, and vaccine development. This manuscript explores AI's multifaceted applications during infectious outbreaks, from predictive modeling outbreak forecasting to acceleration development antimicrobial resistance detection. AI-driven technologies, including deep learning reinforcement learning, have shown remarkable effectiveness improving diagnostic accuracy, streamlining discovery processes, providing real-time decision-making support for healthcare providers. However, despite its substantial contributions, deployment AI pandemic faces key limitations, concerns about data privacy, model transparency, need constant updates adapt emerging pathogens. The integration with human expertise is essential optimize global health outcomes address these challenges. review highlights both potential obstacles fully leveraging response, proposing pathways overcoming current limitations maximizing impact on future outbreaks.
Language: Английский
Citations
0
Methods in microbiology, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 1, 2025
Language: Английский
Citations
0