Records 1-30 (of 51 Records) |
Query Trace: Consumer or personal genomics[original query] |
---|
CovidRhythm: A Deep Learning Model for Passive Prediction of Covid-19 Using Biobehavioral Rhythms Derived From Wearable Physiological Data. Sarwar Atifa, et al. IEEE open journal of engineering in medicine and biology 2023 0 0. 21-30 |
Adoption of Digital Vaccination Services: It Is the Click Flow, Not the Value-An Empirical Analysis of the Vaccination Management of the COVID-19 Pandemic in Germany. Alscher Alexander, et al. Vaccines 2023 0 0. (4) |
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. |
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 |
A Scoping Review of Digital Health Interventions for Combating COVID-19 Misinformation and Disinformation. Czerniak Katarzyna, et al. Journal of the American Medical Informatics Association : JAMIA 2023 0 0. |
Improving Public Health Policy by Comparing the Public Response during the Start of COVID-19 and Monkeypox on Twitter in Germany: A Mixed Methods Study. Al-Ahdal Tareq, et al. Vaccines 2022 0 0. (12) |
Analysis of the domestic market for COVID-19 diagnostic kits by real-time reverse-transcription polymerase chain reaction. Zhigaleva Ol'ga Nikolaevna, et al. Klinicheskaia laboratornaia diagnostika 2022 0 0. (11) 672-677 |
Predicting factors affecting the intention to use a 3PL during the COVID-19 pandemic: A machine learning ensemble approach. German Josephine D, et al. Heliyon 2022 0 0. (11) e11382 |
Source Credibility Theory: SME Hospitality Sector Blog Posting During the Covid-19 Pandemic. Serman Zehra Ece, et al. Information systems frontiers : a journal of research and innovation 2022 0 0. 1-18 |
Global estimates of the fitness advantage of SARS-CoV-2 variant Omicron. van Dorp Christiaan, et al. Virus evolution 2022 0 0. (2) veac089 |
SARS-CoV-2 Variants Monitoring Using Real-Time PCR. Esman Anna, et al. Diagnostics (Basel, Switzerland) 2022 0 0. (10) |
COVID-19 Epidemiology and Diagnosis: Monitoring Evolutionary Changes in the SARS-COV-2 Virus. Akimkin V G, et al. Herald of the Russian Academy of Sciences 2022 0 0. (4) 392-397 |
Telehealth Perceptions Among US Immigrant Patients at an Academic Internal Medicine Practice: Cross-sectional Study. Levine Susan, et al. JMIR human factors 2022 0 0. (3) e36069 |
A Perspective of COVID-19 and Healthcare: Using Social Media Data and an Aspect-based Sentiment Analysis for Usability Evaluation of a Wearable Mixed Reality Headset. Jeong Heejin, et al. JMIR serious games 2022 0 0. |
Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough. Ponomarchuk Alexander, et al. IEEE journal of selected topics in signal processing 2022 0 0. (2) 175-187 |
Prediction of electricity energy consumption including COVID-19 precautions using the hybrid MLR-FFANN optimized with the stochastic fractal search with fitness distance balance algorithm. Dalcali Adem, et al. Concurrency and computation : practice & experience 2022 0 0. e6947 |
Consumer-grade wearables identify changes in multiple physiological systems during COVID-19 disease progression C Mayer, et al, Cell Reports and Medicine, April 19, 2022
Consumer-grade wearables are needed to track disease, especially in the ongoing pandemic, as they can monitor patients in real time. We show that decomposing heart rate from low-cost wearable technologies into signals from different systems can give a multidimensional description of physiological changes due to COVID-19 infection. We find that the separate physiological features of basal heart rate, heart rate response to physical activity, circadian variation in heart rate, and autocorrelation of heart rate are significantly altered and can classify symptomatic versus healthy periods. Increased heart rate and autocorrelation begin at symptom onset, while the heart rate response to activity increases soon after symptom onset and increases more in individuals exhibiting cough. Symptom onset is associated with a blunting of circadian variation in heart rate, as measured by the uncertainty in the phase estimate.
|
Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study. Mason Ashley E, et al. Scientific reports 2022 0 0. (1) 3463 |
Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study AE Mason et al, Scientific Reports, March 2, 2022
Early detection of diseases such as COVID-19 could be a critical tool in reducing disease transmission by helping individuals recognize when they should self-isolate, seek testing, and obtain early medical intervention. Consumer wearable devices that continuously measure physiological metrics hold promise as tools for early illness detection. We gathered daily questionnaire data and physiological data using a consumer wearable (Oura Ring) from 63,153 participants, of whom 704 self-reported possible COVID-19 disease.
|
A deep LSTM network for the Spanish electricity consumption forecasting. Torres J F, et al. Neural computing & applications 2022 0 0. 1-13 |
Search Like an Expert: Reducing Expertise Disparity Using a Hybrid Neural Index for COVID-19 Queries. Nguyen Vincent, et al. Journal of biomedical informatics 2022 0 0. 104005 |
Recommendation agents and information sharing through social media for coronavirus outbreak. Nilashi Mehrbakhsh, et al. Telematics and informatics 2021 0 0. 101597 |
What is the impact of service quality on customers' satisfaction during COVID-19 outbreak? New findings from online reviews analysis. Nilashi Mehrbakhsh, et al. Telematics and informatics 2021 0 0. 101693 |
Browser-based Data Annotation, Active Learning, and Real-Time Distribution of Artificial Intelligence Models: From Tumor Tissue Microarrays to COVID-19 Radiology. Bhawsar Praphulla M S, et al. Journal of pathology informatics 2021 0 0. 38 |
Web-based internet searches for digital health products in the United Kingdom before and during the COVID-19 pandemic: a time-series analysis using app libraries from the Organisation for the Review of Care and Health Applications (ORCHA). Leigh Simon, et al. BMJ open 2021 0 0. (10) e053891 |
COVID-19: protocol for observational studies utilizing near real-time electronic Australian general practice data to promote effective care and best-practice policy-a design thinking approach. Georgiou Andrew, et al. Health research policy and systems 2021 0 0. (1) 122 |
Feature Augmented Hybrid CNN for Stress Recognition Using Wrist-based Photoplethysmography Sensor. Rashid Nafiul, et al. ArXiv 2021 0 0. |
Innovative preclinic triage system to guide Australians to the right mental health care first time. Davenport Tracey A, et al. Australian health review : a publication of the Australian Hospital Association 2021 0 0. |
Envisioning Insight-Driven Learning Based on Thick Data Analytics With Focus on Healthcare. Fiaidhi Jinan, et al. IEEE access : practical innovations, open solutions 2021 0 0. 114998-115004 |
COVID-19 – Protocol for Observational Studies Utilising Near Real-Time Electronic Australian General Practice Data to Promote Effective Care and Best-Practice Policy – A Design Thinking Approach Georgiou, Andrew et al. Research Square January 13 2021 |
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 18, 2024
- Content source: