Infectious Medicine, Journal Year: 2024, Volume and Issue: 3(4), P. 100151 - 100151
Published: Nov. 9, 2024
Language: Английский
Computation, Journal Year: 2025, Volume and Issue: 13(2), P. 53 - 53
Published: Feb. 13, 2025
Integrating artificial intelligence (AI) into public health has emerged as a transformative force, reshaping how data are collected, analyzed, and utilized [...]
Language: Английский
Citations
1
Small Structures, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 19, 2025
To effectively address crisis emergence of new virus such as monkeypox, a collective and collaborative effort between scientists, engineers, innovators, artists from all ages, regions, diverse fields is required. This review explores holistic approach to addressing the monkeypox by integrating nanobiosensors, artificial intelligence, visual arts, humanities, social sciences. Traditional diagnostic methods are often limited time, accessibility, accuracy, but advancement point‐of‐care smart nanobiosensors offers promising shift toward rapid, precise, accessible diagnostics. They enhance ability screen, diagnose, monitor infections efficiently, contributing better disease management. Beyond technological innovation, essential role sciences in fostering public engagement, understanding, acceptance tools emphasized. Visual arts can illustrate scientific concepts, making them more relatable, while storytelling through various media reduce stigma promote preventive measures. Social provide insights into cultural attitudes, behaviors, health challenges, ensuring that solutions integrated communities. By combining these disciplines, this presents comprehensive framework for resilient global system aligns with One Health principles, emphasizing interconnectedness human, animal, environmental health.
Language: Английский
Citations
1
Seminars in Nuclear Medicine, Journal Year: 2025, Volume and Issue: unknown
Published: March 1, 2025
Language: Английский
Citations
1
BMJ Global Health, Journal Year: 2025, Volume and Issue: 10(1), P. e015693 - e015693
Published: Jan. 1, 2025
Gross domestic product (GDP) has been shown to affect government spending on various budget heads including healthcare and the purchase distribution of vaccines. This vulnerable situation exacerbated by COVID-19 pandemic which disrupted exposed fragile nature equitable access vaccines for childhood immunisation globally. A systematic review meta-analysis assess association country income status GDP with vaccination coverage other major infectious diseases around globe will inform global national policy equity in living standards vaccine uptake. study was carried out identify factors influenced that access, distribution, uptake world using a approach. Data were extracted burden programmes, affecting vaccines, procurement platforms, percentage used Factors influencing rate also assessed. The protocol registered PROSPERO (ID: CRD42022350418) Preferred Reporting Items Systematic Reviews Meta-Analyses guidelines. from 195 countries showed following had highest burden; human papillomavirus (HPV), measles, Ebola yellow fever. Low-income some lower-middle-income (LMICs) COVAX UNICEF while high-income (HICs) preferred regional public tenders. Global tuberculosis, diphtheria/tetanus/pertussis, hepatitis B, Haemophilus influenzae type b, polio, meningitis HPV significantly higher than COVID-19. Being an HIC having data collected 1985 2015 as most current associated high coverage. spent did not influence LMICs should prioritise research improve development capacity. Countries worldwide share expenditure, coverage, introduction new technologies facilitate access.
Language: Английский
Citations
0
IntechOpen eBooks, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 23, 2025
The COVID-19 pandemic significantly disrupted glioblastoma (GBM) management, affecting its pathophysiology, diagnosis, treatment, and prognosis. GBM, an aggressive brain tumor with poor survival rates, presented unique vulnerabilities during the due to rapid progression patients’ compromised immunity. SARS-CoV-2 may also influence GBM by binding overexpressed receptors on cells, potentially activating oncogenic pathways. This interaction highlights potential for exacerbate aggressiveness. Diagnostic delays resulted in increased volumes, while treatment pathways adapted minimally invasive surgeries, hypofractionated radiotherapy, telemedicine ensure continuity of care. Despite these innovations, outcomes varied globally, centers adopting flexible protocols reporting fewer adverse impacts. Vaccination emerged as a critical tool, prioritization patients minimal effects, providing protection against severe COVID-19. paper explores multifaceted impact detailing disruptions strategies that paved way resilient neuro-oncological care after pandemic.
Language: Английский
Citations
0
Deleted Journal, Journal Year: 2025, Volume and Issue: 3(3), P. 4 - 13
Published: April 17, 2025
The relaxation of online prescription medicine sales policies is expected to drive significant growth in Pharma 4.0 platforms, which serve as crucial terminals for medications. However, since pharmaceuticals directly impact public health and safety, their entire supply chain must maintain strict traceability. This article assesses the current state pharmaceutical industry logistics Pakistan analyzes unique requirements drug distribution systems, differ from traditional due specialized nature medical products. Building on established practices developed nations like U.S. Japan, study proposes a chain-based framework examines its operational workflow. Furthermore, by integrating internet things (IoT) technology, system incorporates delivery information platform that uses electronic supervision codes enable standardized identification real-time tracking, ensuring full traceability throughout distribution. Through collaborative mechanisms, guarantees medications reach patients safely, efficiently, compliance with regulatory standards.
Language: Английский
Citations
0
The International Journal of Health Planning and Management, Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 27, 2024
Abstract Artificial intelligence (AI) applications are complex and rapidly evolving, thus often poorly understood, but have potentially profound implications for public health. We offer a primer health professionals that explains some of the key concepts involved examines how these might be used in response to future pandemic. They include early outbreak detection, predictive modelling, healthcare management, risk communication, surveillance. applications, especially algorithms, ability anticipate outbreaks by integrating diverse datasets such as social media, meteorological data, mobile phone movement data. intelligence‐powered tools can also optimise delivery managing allocation resources reducing workers' exposure risks. In resource distribution, they demand logistics, while AI‐driven robots minimise physical contact settings. shows promise supporting decision‐making simulating economic impacts different policy interventions. These simulations help policymakers evaluate scenarios lockdowns allocation. Additionally, it enhance messaging, with AI‐generated communications shown more effective than human‐generated messages cases. However, there risks, privacy concerns, biases models, potential ‘false confirmations’, where AI reinforces incorrect decisions. Despite challenges, we argue will become increasingly important crises, only if integrated thoughtfully into existing systems processes.
Language: Английский
Citations
3
Decoding Infection and Transmission, Journal Year: 2024, Volume and Issue: 2, P. 100026 - 100026
Published: Jan. 1, 2024
Language: Английский
Citations
3
Healthcare, Journal Year: 2024, Volume and Issue: 12(17), P. 1694 - 1694
Published: Aug. 26, 2024
Background: COVID-19 has had a substantial influence on healthcare systems, requiring early prognosis for innovative therapies and optimal results, especially in individuals with comorbidities. AI systems have been used by practitioners investigating, anticipating, predicting diseases, through means including medication development, clinical trial analysis, pandemic forecasting. This study proposes the use of to predict disease severity terms hospital mortality among patients. Methods: A cross-sectional was conducted at King Abdulaziz University, Saudi Arabia. Data were cleaned encoding categorical variables replacing missing quantitative values their mean. The outcome variable, mortality, labeled as death = 0 or survival 1, all baseline investigations, symptoms, laboratory findings predictors. Decision trees, SVM, random forest algorithms employed. training process included splitting data set into testing sets, performing 5-fold cross-validation tune hyperparameters, evaluating performance test using accuracy. Results: assessed predictive accuracy outcomes patients based factors such CRP, LDH, Ferritin, ALP, Bilirubin, D-Dimers, stay (p-value ≤ 0.05). analysis revealed that stay, Ferritin significantly influenced (p 0.0001). results demonstrated high accuracy, decision trees achieving 76%, 80%, support vector machines (SVMs) 82%. Conclusions: Artificial intelligence is tool crucial identifying coronavirus infections monitoring patient conditions. It improves treatment consistency decision-making via development algorithms.
Language: Английский
Citations
2
Journal of Virological Methods, Journal Year: 2024, Volume and Issue: 330, P. 115011 - 115011
Published: Aug. 16, 2024
Language: Английский
Citations
1