Опубликована: Окт. 3, 2024
Язык: Английский
Engineering Science & Technology Journal, Год журнала: 2024, Номер 5(5), С. 1794 - 1816
Опубликована: Май 21, 2024
Natural disasters often lead to significant disruptions in healthcare delivery, exacerbating the already formidable challenges faced by systems. Leveraging artificial intelligence (AI) offers a promising approach mitigate these and enhance management during after natural disasters. This conceptual paper aims propose framework for integration of AI into disaster response efforts, with focus on optimizing resource allocation, improving patient triage, enhancing overall system resilience. Through comprehensive review existing literature, this identifies gaps current practices explores potential address shortcomings. By analyzing case studies examples from previous disasters, highlights transformative impact that technologies such as predictive analytics, machine learning, robotics can have delivery crisis situations. The objectives are twofold: define strategic incorporating protocols outline expected outcomes implementing framework. Expected benefits include expedited triage processes, more accurate improved communication systems, ultimately leading better enhanced efficiency. proposed emphasizes importance interdisciplinary collaboration between professionals, technologists, policymakers, experts. It also addresses ethical considerations associated implementation settings. In conclusion, underscores critical role bolstering capabilities leveraging technologies, systems become adaptive, responsive, resilient face unforeseen challenges, saving lives minimizing communities. Keywords: AI-Enhanced Healthcare Management, Disasters, Conceptual Insights.
Язык: Английский
Процитировано
23
International Medical Science Research Journal, Год журнала: 2024, Номер 4(6), С. 647 - 667
Опубликована: Июнь 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.
Язык: Английский
Процитировано
19
Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(6), С. 1314 - 1334
Опубликована: Июнь 7, 2024
The integration of artificial intelligence (AI) into HIV treatment regimens has revolutionized the approach to personalized care and optimization strategies. This study presents an in-depth analysis role AI in transforming treatment, focusing on its ability tailor therapy individual patient needs enhance outcomes. AI-driven involves utilization advanced algorithms computational techniques analyze vast amounts data, including genetic information, viral load measurements, history. By harnessing power machine learning predictive analytics, can identify patterns trends data that may not be readily apparent human clinicians. One key benefits is personalize based characteristics disease progression. considering factors such as drug resistance profiles, comorbidities, lifestyle factors, recommend most effective well-tolerated options for each patient, leading improved adherence clinical Furthermore, enables continuous monitoring adjustment real time, allowing healthcare providers respond rapidly changes status evolving dynamics. proactive management help prevent failure development resistance, ultimately better long-term outcomes patients. Despite transformative potential, without challenges. Ethical considerations, privacy concerns, need robust validation regulatory oversight are all important must addressed ensure safe implementation practice. In conclusion, integrative presented this underscores significant impact personalization regimens. leveraging technologies, approaches needs, quality life people living with HIV. Keywords: Integrative Analysis, AI- Driven, Optimization, Treatment, Regimens.
Язык: Английский
Процитировано
19
International Journal of Frontiers in Life Science Research, Год журнала: 2024, Номер 6(1), С. 022 - 035
Опубликована: Март 26, 2024
This paper explores the integration of IoT devices, data analytics, and education techniques to enhance pediatric dental health outcomes. By leveraging real-time collection, analysis, personalized interventions, can empower both caregivers children adopt proactive hygiene practices. comprehensive approach not only improves oral but also establishes lifelong habits for overall wellness. Pediatric is a vital often overlooked component well-being. Despite its significance, it frequently lacks attention deserves. Integrating Internet Things (IoT) technologies into care presents an opportunity substantial improvement in early prevention strategies. enhances conducive crucial determinant well-being, yet remains overshadowed by other priorities. Addressing requires measures, including The promising avenue revolutionize delves potential improving health. harnessing empowers holistic fosters development Through examination integration, this underscores transformative impact have on health, emphasizing importance prioritizing innovative approaches address critical aspect childhood
Язык: Английский
Процитировано
12
Journal of Integrated Care, Год журнала: 2025, Номер unknown
Опубликована: Янв. 16, 2025
Purpose The COVID-19 pandemic significantly reshaped the healthcare landscape, revealing both systemic strengths and weaknesses. This article examines a long-term study of pandemic’s impacts on systems integrated care processes, highlighting negative results – such as increased burnout persistent flaws positive outcomes, improved patient models, enhanced collaboration technological integration. Design/methodology/approach employed elements ethnographic approach, combining various qualitative methods with literature review data analysis. Findings findings reveal mixed legacy: while accelerated innovation exposed flaws, it also exacerbated mental health issues among workers. Research limitations/implications main limitation is study’s focus Polish system, which may introduce biases limit generalizability to other regions different backgrounds, infrastructures responses. Practical implications Addressing these will be crucial for developing robust policies improving overall delivery processes. Social provides practical policymakers, providers workforce, emphasizing need structural resilience, effective resource management ongoing professional development sustain enhance globally. Originality/value originality arises from its methodological interviews professionals narrative provide analysis outcomes pandemic, particularly focusing system generalizing insights that could relevant
Язык: Английский
Процитировано
0
Health information science, Год журнала: 2025, Номер unknown, С. 183 - 211
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Data & Metadata, Год журнала: 2025, Номер 4, С. 633 - 633
Опубликована: Март 19, 2025
Introduction: Before the COVID-19 pandemic, telemedicine and telehealth faced legal, technological, cultural regulatory limitations. The health crisis boosted its massive adoption, enhancing continuity over time. objective of this review is to determine projections in post-COVID-19 era factors that condition growth.Methods: A systematic was carried out following PRISMA-ScR guidelines. databases consulted were PubMed, Web Science, Scopus. 19 relevant studies selected from an initial total 96.Results: pandemic accelerated adoption telemedicine, maintaining use areas such as mental chronic diseases. Factors associated with development technologies, added economic aspects, have hindered growth.Conclusions: Telehealth improved access health, but their sustainability requires resolving technological inequalities, addition guaranteeing privacy security standards.
Язык: Английский
Процитировано
0
IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 203 - 220
Опубликована: Март 7, 2025
This chapter explores how technology is transforming cancer education and support for survivors healthcare providers. It covers innovations like mobile apps, telemedicine, AI, virtual reality, social media, highlighting their impact on sharing information, offering support, delivering care. Through literature reviews, case studies, research, the assesses effectiveness of these tools in improving patient outcomes, enhancing provider education, creating a more connected care community. also addresses challenges digital literacy, accessibility, data privacy, insights professionals, policymakers, tech developers to optimize
Язык: Английский
Процитировано
0
The Egyptian Journal of Internal Medicine, Год журнала: 2025, Номер 37(1)
Опубликована: Май 20, 2025
Abstract Background The review paper explores the evolution, benefits, and challenges of telemedicine within U.S. healthcare system. Originally developed to address needs remote underserved populations, has seen significant expansion, particularly during COVID-19 pandemic. Method This synthesizes recent literature assess telemedicine’s impact on access, quality, equity. Findings findings indicate that significantly enhanced for chronic disease management mental health services, but also reveal such as regulatory barriers, technological limitations, disparities in especially rural areas. Additionally, highlights need a unified national policy, robust data security measures, targeted interventions ensure equitable access. Conclusion concludes while offers transformative potential, realizing its full benefits requires addressing these systemic through collaboration among policymakers, providers, researchers.
Язык: Английский
Процитировано
0
International Medical Science Research Journal, Год журнала: 2024, Номер 4(5), С. 544 - 557
Опубликована: Май 5, 2024
Vaccine distribution in resource-limited settings remains a crucial global health challenge, exacerbated by factors such as inadequate infrastructure, limited resources, and complex supply chains. Leveraging machine learning (ML) holds promise for optimizing efficiency ensuring equitable access to life-saving vaccines. This paper synthesizes various ML approaches aimed at addressing vaccine challenges resource-constrained environments. The literature review examines existing research on applications healthcare distribution, highlighting key findings methodologies. Methodologically, criteria were established selecting relevant studies, with focus techniques their effectiveness contexts. Key identified include predictive analytics demand forecasting, route optimization algorithms efficient delivery, decision support systems prioritizing efforts. Case studies illustrate successful implementations real-world settings, showcasing improved coverage reduced wastage. Despite promising results, persist, including data scarcity, model generalization, ethical considerations. Future directions enhancing collection methods, refining specific contexts, integrating solutions into systems. In conclusion, this synthesis underscores the transformative potential of revolutionizing settings. By logistical barriers resource allocation, ML-driven offer pathway towards achieving universal immunization mitigating impact infectious diseases vulnerable populations. Keywords: Machine Learning, Distribution, Resource-Limited Settings, Synthesis Approaches.
Язык: Английский
Процитировано
2