Records 1-30 (of 270 Records) |
Query Trace: APP[original query] |
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An AI healthcare ecosystem framework for Covid-19 detection and forecasting using CronaSona. Hassan Samah A Z, et al. Medical & biological engineering & computing 2024 0 0. |
Digital health for remote home monitoring of patients with COVID-19 requiring oxygen: a cohort study and literature review. Chaytee Johann, et al. Frontiers in medicine 2024 0 0. 1255798 |
Predicting subnational incidence of COVID-19 cases and deaths in EU countries. Robert Alexis, et al. BMC infectious diseases 2024 0 0. (1) 204 |
Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts. Luca Ferretti et al. Nature 2023 12
From the abstract: "Here we analysed 7 million contacts notified by the NHS COVID-19 app6,7 in England and Wales to infer how app measurements translated to actual transmissions. Empirical metrics and statistical modelling showed a strong relation between app-computed risk scores and actual transmission probability. Longer exposures at greater distances had similar risk to shorter exposures at closer distances. The probability of transmission confirmed by a reported positive test increased initially linearly with duration of exposure (1.1% per hour) and continued increasing over several days. "
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Unsupervised machine learning to investigate trajectory patterns of COVID-19 symptoms and physical activity measured via the MyHeart Counts App and smart devices. Varsha Gupta et al. NPJ Digit Med 2023 12 (1) 239
From the abstract: " Previous studies have associated COVID-19 symptoms severity with levels of physical activity. We therefore investigated longitudinal trajectories of COVID-19 symptoms in a cohort of healthcare workers (HCWs) with non-hospitalised COVID-19 and their real-world physical activity. 121 HCWs with a history of COVID-19 infection who had symptoms monitored through at least two research clinic visits, and via smartphone were examined. HCWs with a compatible smartphone were provided with an Apple Watch Series 4 and were asked to install the MyHeart Counts Study App to collect COVID-19 symptom data and multiple physical activity parameters"
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Use of a digital contact tracing system in Singapore to mitigate COVID-19 spread. Chow Bryan W K, et al. BMC public health 2023 0 0. (1) 2253 |
Machine learning identifies a COVID-19-specific phenotype in university students using a mental health app. Shvetcov Artur, et al. Internet interventions 2023 0 0. 100666 |
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). "
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Can digital health researchers make a difference during the pandemic? Results of the single-arm, chatbot-led Elena+: Care for COVID-19 interventional study. Ollier Joseph, et al. Frontiers in public health 2023 0 0. 1185702 |
Implementing and Maintaining a SARS-CoV-2 Exposure Notification Application for Mobile Phones: The Finnish Experience. Pihlajamäki Mika, et al. JMIR public health and surveillance 2023 0 0. e46563 |
Feasibility of using intermittent active monitoring of vital signs by smartphone users to predict SARS-CoV-2 PCR positivity. Dolezalova Nikola, et al. Scientific reports 2023 0 0. (1) 10581 |
Digital Public Health Solutions in Response to the COVID-19 Pandemic: Comparative Analysis of Contact Tracing Solutions Deployed in Japan and Germany. Louw Candice, et al. Journal of medical Internet research 2023 0 0. e44966 |
SARS-CoV-2 viral RNA detection using the novel CoVradar device associated with the CoVreader smartphone app. Martín-Sierra Carmen, et al. Biosensors & bioelectronics 2023 0 0. 115268 |
Classification of Patient Recovery from COVID-19 Symptoms using Consumer Wearables and Machine Learning. Leitner Jared, et al. IEEE journal of biomedical and health informatics 2023 0 0. |
Using Wearable Technology to Quantify Physical Activity Recovery: Secondary Report From the AFTER (App-Facilitated Tele-Rehabilitation) Program for COVID-19 Survivors Randomized Study. Churchill Laura, et al. JMIR rehabilitation and assistive technologies 2023 0 0. e43436 |
Severity and mortality prediction models to triage Indian COVID-19 patients. Bhatia Samarth, et al. PLOS digital health 2023 0 0. (3) e0000020 |
Protocol for an OpenSAFELY cohort study collecting patient-reported outcome measures using the TPP Airmid smartphone application and linked big data to quantify the health and economic costs of long COVID (OpenPROMPT). Herrett Emily, et al. BMJ open 2023 0 0. (2) e071261 |
A digital health platform to manage COVID-19: decentralizing technology to empower rural and remote jurisdictions. Katapally Tarun, et al. Rural and remote health 2023 0 0. (1) 8097 |
Early peripheral blood MCEMP1 and HLA-DRA expression predicts COVID-19 prognosis. Chan Kuan Rong, et al. EBioMedicine 2023 0 0. 104472 |
Epidemiological impacts of the NHS COVID-19 app in England and Wales throughout its first year M Kendall et al, Nat Comm, February 22, 2023
The NHS COVID-19 app was launched in England and Wales in September 2020, with a Bluetooth-based contact tracing functionality designed to reduce transmission of SARS-CoV-2. We show that user engagement and the app’s epidemiological impacts varied according to changing social and epidemic characteristics throughout the app’s first year. We describe the interaction and complementarity of manual and digital contact tracing approaches.
We estimate that the app’s contact tracing function alone averted about 1 million cases (sensitivity analysis 450,000–1,400,000) during its first year, corresponding to 44,000 hospital cases (SA 20,000–60,000) and 9,600 deaths (SA 4600–13,000).
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The feasibility of digital health approach to facilitate remote dental screening among preschool children during COVID-19 and social restrictions. Azimi Somayyeh, et al. International journal of paediatric dentistry 2023 0 0. |
Has the pandemic enhanced and sustained digital health-seeking behaviour? A big-data interrupted time-series analysis of Google Trends. van Kessel Robin, et al. Journal of medical Internet research 2023 0 0. |
Development and Validation of Simple Risk Scores to Predict Hospitalization in Outpatients with COVID-19 Including the Omicron Variant. Ebell Mark H, et al. Journal of the American Board of Family Medicine : JABFM 2022 0 0. (6) 1058-1064 |
Associations of country-specific and sociodemographic factors with self-reported COVID-19-related symptoms: Multivariable analysis of data from the CoronaCheck mobile health platform. Humer Elke, et al. JMIR public health and surveillance 2022 0 0. |
Sewershed surveillance as a tool for smart management of a pandemic in threshold countries. Case study: Tracking SARS-CoV-2 during COVID-19 pandemic in a major urban metropolis in northwestern Argentina. Cruz Mercedes Cecilia, et al. The Science of the total environment 2022 0 0. 160573 |
Colorimetric Detection of SARS-CoV-2 Using Plasmonic Biosensors and Smartphones. Materón Elsa M, et al. ACS applied materials & interfaces 2022 0 0. |
Contextual counters and multimodal Deep Learning for activity-level traffic classification of mobile communication apps during COVID-19 pandemic. Guarino Idio, et al. Computer networks 2022 0 0. 109452 |
ActiveHip+: A feasible mHealth system for the recovery of older adults after hip surgery during the COVID-19 pandemic. Prieto-Moreno Rafael, et al. Digital health 2022 0 0. 20552076221139694 |
COVID-19 smart surveillance: Examination of Knowledge of Apps and mobile thermometer detectors (MTDs) in a high-risk society. Sayibu Muhideen, et al. Digital health 2022 0 0. 20552076221132092 |
Risk factors and symptom clusters for Long Covid: analysis of United Kingdom symptom tracker app data. E Ford et al, MEDRXIV, November 14, 2022
4,040 participants reporting for >4 months in the Covid Symptom Study App were included. Multivariate logistic regression was undertaken to identify risk factors associated with Long Covid. Cluster analysis and factor analysis were undertaken to investigate symptom clusters. Results: Long Covid affected 13.6% of participants. Significant risk factors included being female (P < 0.01), pre-existing poor health (P < 0.01), and worse symptoms in the initial illness. A model incorporating sociodemographics, comorbidities, and health status predicted Long Covid with an accuracy (AUROC) of 76%.
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