Records 1-30 (of 571 Records) |
Query Trace: Big data or precision health[original query] |
---|
Using mobile phone big data to discover the spatial patterns of rural migrant workers' return to work in China's three urban agglomerations in the post-COVID-19 era. Liu Kai, et al. Environment and planning. B, urban analytics and city science 2024 0 0. (4) 878-894 |
Proteome profiling of home-sampled dried blood spots reveals proteins of SARS-CoV-2 infections. Claudia Fredolini et al. Commun Med (Lond) 2024 4 (1) 55
From the abstract: "Our three studies display highly consistent variance of protein levels and share associations of proteins with sex (e.g., MMP3) and age (e.g., GDF-15). Studying seropositive (IgG+) and seronegative (IgG-) donors from the first pandemic wave reveals a network of proteins reflecting immunity, inflammation, coagulation, and stress response. Proteome analysis of volumetric self-sampled DBS facilitates precise analysis of clinically relevant proteins, including those secreted into the circulation or found on blood cells, augmenting previous COVID-19 reports with clinical blood collections. Our population surveys support the usefulness of DBS, underscoring the role of timing the sample collection to complement clinical and precision health monitoring initiatives. "
|
The impact of comorbidities and economic inequality on COVID-19 mortality in Mexico: a machine learning approach. Méndez-Astudillo Jorge, et al. Frontiers in big data 2024 0 0. 1298029 |
Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review. Clark Emily C, et al. JMIR public health and surveillance 2024 0 0. e49185 |
The Accuracy of Predictive Analytics in Forecasting Emergency Department Volume Before and After Onset of COVID-19. Napoli Anthony M, et al. The western journal of emergency medicine 2024 0 0. (1) 61-66 |
Drug prescription patterns and their association with mortality and hospitalization duration in COVID-19 patients: insights from big data. Mehrizi Reza, et al. Frontiers in public health 2024 0 0. 1280434 |
Ensemble learning for multi-class COVID-19 detection from big data. Kaleem Sarah, et al. PloS one 2023 0 0. (10) e0292587 |
Engaging a national-scale cohort of smart thermometer users in participatory surveillance YJ Tseng et al, NPJ Digital Medicine, September 20, 2023
From the abstract: "Participatory surveillance systems crowdsource individual reports to rapidly assess population health phenomena. The value of these systems increases when more people join and persistently contribute. We examine the level of and factors associated with engagement in participatory surveillance among a retrospective, national-scale cohort of individuals using smartphone-connected thermometers with a companion app that allows them to report demographic and symptom information. Between January 1, 2020 and October 29, 2022, 1,325,845 participants took 20,617,435 temperature readings, yielding 3,529,377 episodes of consecutive readings. There were 1,735,805 (49.2%) episodes with self-reported symptoms (including reports of no symptoms). "
|
Big data evidence of the impact of COVID-19 hospitalizations on mortality rates of non-COVID-19 critically ill patients. Wichmann Bruno, et al. Scientific reports 2023 0 0. (1) 13613 |
IT Capabilities, Strategic Flexibility and Organizational Resilience in SMEs Post-COVID-19: A Mediating and Moderating Role of Big Data Analytics Capabilities. Wided Ragmoun, et al. Global journal of flexible systems management 2023 0 0. (1) 123-142 |
Fib-4 score is able to predict intra-hospital mortality in 4 different SARS-COV2 waves. Miele Luca, et al. Internal and emergency medicine 2023 0 0. |
Measuring human mobility in times of trouble: an investigation of the mobility of European populations during COVID-19 using big data. Guardabascio Barbara, et al. Quality & quantity 2023 0 0. 1-19 |
Severe coronavirus disease 2019 in pediatric solid organ transplant recipients: Big data convergence study in Korea (K-COV-N cohort). Kang Ji-Man, et al. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases 2023 0 0. |
Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data. Hua Lei, et al. Frontiers in public health 2023 0 0. 1029385 |
COVID-19 contact tracking based on person reidentification and geospatial data. Zhang Boxing, et al. Journal of King Saud University. Computer and information sciences 2023 0 0. (5) 101558 |
A Systematic Literature Review and Future Perspectives for Handling Big Data Analytics in COVID-19 Diagnosis. Tenali Nagamani, et al. New generation computing 2023 0 0. (2) 243-280 |
CoVEffect: interactive system for mining the effects of SARS-CoV-2 mutations and variants based on deep learning. Serna García Giuseppe, et al. GigaScience 2023 0 0. |
Forecasting the Spread of COVID-19 Using Deep Learning and Big Data Analytics Methods. Kiganda Cylas, et al. SN computer science 2023 0 0. (4) 374 |
Exploring Future Signals of COVID-19 and Response to Information Diffusion Using Social Media Big Data. Song Juyoung, et al. International journal of environmental research and public health 2023 0 0. (9) |
A high-frequency mobility big-data reveals how COVID-19 spread across professions, locations and age groups. Zhao Chen, et al. PLoS computational biology 2023 0 0. (4) e1011083 |
Public Perception Before and After COVID-19 Vaccine Pass for the Unvaccinated to Eat Alone: Social Media Data Analytics. Jung Sun Ok, et al. Inquiry : a journal of medical care organization, provision and financing 2023 0 0. 469580231169407 |
Predicting Prolonged Hospital Stays in Elderly Patients With Hip Fractures Managed During the COVID-19 Pandemic in Chile: An Artificial Neural Networks Study. Diaz-Ledezma Claudio, et al. HSS journal : the musculoskeletal journal of Hospital for Special Surgery 2023 0 0. (2) 205-209 |
A big data analysis of COVID-19 impacts on Airbnbs' bookings behavior applying construal level and signaling theories. Filieri Raffaele, et al. International journal of hospitality management 2023 0 0. 103461 |
Big data are needed for analysis of the association of retinal vascular occlusion and COVID-19. Chung Yoo-Ri, et al. Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie 2023 0 0. 1-2 |
OzNet: A New Deep Learning Approach for Automated Classification of COVID-19 Computed Tomography Scans. Ozaltin Oznur, et al. Big data 2023 0 0. |
A CoviReader Architecture Based on IOTA Tangle for Outbreak Control in Smart Cities during COVID-19 Pandemic. Alhavan Maryam, et al. Medical journal of the Islamic Republic of Iran 2023 0 0. 180 |
Minimizing Viral Transmission in COVID-19 Like Pandemics: Technologies, Challenges, and Opportunities. Nisar Shibli, et al. IEEE sensors journal 2023 0 0. (2) 922-932 |
Effect of the chronic medication use on outcome measures of hospitalized COVID-19 patients: Evidence from big data. Malekpour Mohammad-Reza, et al. Frontiers in public health 2023 0 0. 1061307 |
Exploring the Potential of Big Data Analytics in Urban Epidemiology Control: A Comprehensive Study Using CiteSpace. Liu Jun, et al. International journal of environmental research and public health 2023 0 0. (5) |
Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach. Moradi Hamidreza, et al. PloS one 2023 0 0. (3) e0282587 |
Disclaimer: Articles listed in the Public Health
Knowledge Base are selected by the CDC Office of Public Health
Genomics to provide current awareness of the literature and news.
Inclusion in the update does not necessarily represent the views of
the Centers for Disease Control and Prevention nor does it imply
endorsement of the article's methods or findings. CDC and DHHS assume
no responsibility for the factual accuracy of the items presented. The
selection, omission, or content of items does not imply any
endorsement or other position taken by CDC or DHHS. Opinion, findings
and conclusions expressed by the original authors of items included in
the update, or persons quoted therein, are strictly their own and are
in no way meant to represent the opinion or views of CDC or DHHS.
References to publications, news sources, and non-CDC Websites are
provided solely for informational purposes and do not imply
endorsement by CDC or DHHS.
- Page last reviewed:Feb 1, 2024
- Page last updated:May 09, 2024
- Content source: