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Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study
Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study
Victoria Hunter, Allison Shapiro, Devika Chawla, Faye Drawnel, Ernesto Ramirez, Elizabeth Phillips, Sara Tadesse-Bell, Luca Foschini, Vincent Ukachukwu
Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study
Victoria Hunter, Allison Shapiro, Devika Chawla, Faye Drawnel, Ernesto Ramirez, Elizabeth Phillips, Sara Tadesse-Bell, Luca Foschini, Vincent Ukachukwu
Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study
Evidation research aimed to characterize the burden of influenza-like illness using commercial wearable sensor data and investigate the extent to which these data correlate with self-reported illness severity and duration.
Victoria Hunter, Allison Shapiro, Devika Chawla, Faye Drawnel, Ernesto Ramirez, Elizabeth Phillips, Sara Tadesse-Bell, Luca Foschini, Vincent Ukachukwu
Machine Learning COVID-19 Detection from Wearables
Machine Learning COVID-19 Detection from Wearables
Bret Nestor, Jaryd Hunter, Raghu Kainkaryam, Erik Drysdale, Jeffrey B Inglis, Allison Shapiro, Sujay Nagaraj, Marzyeh Ghassemi, Luca Foschini, Anna Goldenberg
Machine Learning COVID-19 Detection from Wearables
Bret Nestor, Jaryd Hunter, Raghu Kainkaryam, Erik Drysdale, Jeffrey B Inglis, Allison Shapiro, Sujay Nagaraj, Marzyeh Ghassemi, Luca Foschini, Anna Goldenberg
Machine Learning COVID-19 Detection from Wearables
Evidation research looks into which criteria must be met before a study can claim reasonable COVID-19 detection performance using data from wearable devices.
Bret Nestor, Jaryd Hunter, Raghu Kainkaryam, Erik Drysdale, Jeffrey B Inglis, Allison Shapiro, Sujay Nagaraj, Marzyeh Ghassemi, Luca Foschini, Anna Goldenberg
Precision Recruitment for High-Risk Participants in a COVID-19 Cohort Study
Precision Recruitment for High-Risk Participants in a COVID-19 Cohort Study
Mezlini A, Caddigan E, Shapiro A, Ramirez E, Kondow-McConaghy H, Yang J, DeMarco K, Naraghi-Arani P, Foschini L
Precision Recruitment for High-Risk Participants in a COVID-19 Cohort Study
Mezlini A, Caddigan E, Shapiro A, Ramirez E, Kondow-McConaghy H, Yang J, DeMarco K, Naraghi-Arani P, Foschini L
Precision Recruitment for High-Risk Participants in a COVID-19 Cohort Study
Evidation describes an approach for reducing recruiting time and resources in a COVID-19 study by targeting recruitment to high-risk individuals.
Mezlini A, Caddigan E, Shapiro A, Ramirez E, Kondow-McConaghy H, Yang J, DeMarco K, Naraghi-Arani P, Foschini L
American Life in Realtime: A Benchmark Registry of Health Data for Equitable Precision Health
American Life in Realtime: A Benchmark Registry of Health Data for Equitable Precision Health
Ritika R. Chaturvedi, Marco Angrisani, Wendy M. Troxel, Tania Gutsche, Eva Ortega, Monika Jain, Adrien Boch & Arie Kapteyn
American Life in Realtime: A Benchmark Registry of Health Data for Equitable Precision Health
Ritika R. Chaturvedi, Marco Angrisani, Wendy M. Troxel, Tania Gutsche, Eva Ortega, Monika Jain, Adrien Boch & Arie Kapteyn
American Life in Realtime: A Benchmark Registry of Health Data for Equitable Precision Health
ALiR, funded by a grant from the NIH, is a first-of-its-kind, publicly available benchmark registry and research infrastructure for person-generated health data collected from smartphones and wearables, made possible by Evidation.
Ritika R. Chaturvedi, Marco Angrisani, Wendy M. Troxel, Tania Gutsche, Eva Ortega, Monika Jain, Adrien Boch & Arie Kapteyn
Predictors of Seeking Care for Influenza-Like Illness in a Novel Digital Study
Predictors of Seeking Care for Influenza-Like Illness in a Novel Digital Study
Devika Chawla, Alejandra Benitez, Hao Xu, Victoria Whitehill, Sara Tadesse-Bell, Allison Shapiro, Ernesto Ramirez, Kelly Scherer, Luca Foschini, Faye Drawnel, Barry Clinch, Marco Prunotto, Vincent Ukachukwu
Predictors of Seeking Care for Influenza-Like Illness in a Novel Digital Study
Devika Chawla, Alejandra Benitez, Hao Xu, Victoria Whitehill, Sara Tadesse-Bell, Allison Shapiro, Ernesto Ramirez, Kelly Scherer, Luca Foschini, Faye Drawnel, Barry Clinch, Marco Prunotto, Vincent Ukachukwu
Predictors of Seeking Care for Influenza-Like Illness in a Novel Digital Study
Evidation conducted a study that used person-generated health data (PGHD) to identify factors associated with seeking care for ILI.
Devika Chawla, Alejandra Benitez, Hao Xu, Victoria Whitehill, Sara Tadesse-Bell, Allison Shapiro, Ernesto Ramirez, Kelly Scherer, Luca Foschini, Faye Drawnel, Barry Clinch, Marco Prunotto, Vincent Ukachukwu
COVID-19 Real-World Evidence Primer
COVID-19 Real-World Evidence Primer
Amy Cavet; Claire Cravero, MPH; Aaron Galaznik, MD; Bray Patrick-Lake, MFS; Aniketh Talwai
COVID-19 Real-World Evidence Primer
Amy Cavet; Claire Cravero, MPH; Aaron Galaznik, MD; Bray Patrick-Lake, MFS; Aniketh Talwai
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COVID-19 Real-World Evidence Primer
Evidation contributed to this online resource consisting of seven chapters that cover types of RWD, methods in RWE generation, examples of RWE studies, and more.
Amy Cavet; Claire Cravero, MPH; Aaron Galaznik, MD; Bray Patrick-Lake, MFS; Aniketh Talwai
What Possibly Affects Nighttime Heart Rate? Conclusions from N-of-1 Observational Data
What Possibly Affects Nighttime Heart Rate? Conclusions from N-of-1 Observational Data
Igor Matias, Eric J. Daza, Katarzyna Wac
What Possibly Affects Nighttime Heart Rate? Conclusions from N-of-1 Observational Data
Igor Matias, Eric J. Daza, Katarzyna Wac
What Possibly Affects Nighttime Heart Rate? Conclusions from N-of-1 Observational Data
Evidation's Lead Biostatistician, Eric J. Daza, worked with the Quality of Life Technology Lab to conduct an n-of-1 study using the MoTR method to evaluate the suggested effects of daily stressors on nighttime heart rate, sleep time, and physical activity in an individualized way.
Igor Matias, Eric J. Daza, Katarzyna Wac
Model-Twin Randomization (MoTR): A Monte Carlo Method for Estimating the Within-Individual Average Treatment Effect Using Wearable Sensors
Model-Twin Randomization (MoTR): A Monte Carlo Method for Estimating the Within-Individual Average Treatment Effect Using Wearable Sensors
Eric J. Daza, Logan Schneider
Model-Twin Randomization (MoTR): A Monte Carlo Method for Estimating the Within-Individual Average Treatment Effect Using Wearable Sensors
Eric J. Daza, Logan Schneider
Model-Twin Randomization (MoTR): A Monte Carlo Method for Estimating the Within-Individual Average Treatment Effect Using Wearable Sensors
In this academic preprint, the model twin randomization (MoTR; "motor") method for analyzing possible causes and effects an individual's intensive longitudinal data is introduced.
Eric J. Daza, Logan Schneider
How Can We Optimise Health Technology Assessment and Reimbursement Decisions to Accelerate Access to New Cardiovascular Medicines?
How Can We Optimise Health Technology Assessment and Reimbursement Decisions to Accelerate Access to New Cardiovascular Medicines?
Martin R. Cowie, Biykem Bozkurt, Javed Butler, Andrew Briggs, Maria Kubin, Adrian Jonas, Amanda I. Adler, Bray Patrick-Lake, Faiez Zannad
How Can We Optimise Health Technology Assessment and Reimbursement Decisions to Accelerate Access to New Cardiovascular Medicines?
Martin R. Cowie, Biykem Bozkurt, Javed Butler, Andrew Briggs, Maria Kubin, Adrian Jonas, Amanda I. Adler, Bray Patrick-Lake, Faiez Zannad
How Can We Optimise Health Technology Assessment and Reimbursement Decisions to Accelerate Access to New Cardiovascular Medicines?
This paper builds on discussions among clinical trialists, industry representatives, regulators, and patients, which took place at the 17th Global Cardiovascular Clinical Trialists (CVCT) Forum in December 2020.
Martin R. Cowie, Biykem Bozkurt, Javed Butler, Andrew Briggs, Maria Kubin, Adrian Jonas, Amanda I. Adler, Bray Patrick-Lake, Faiez Zannad
Cognitive Digital Biomarkers from Automated Transcription of Spoken Language
Cognitive Digital Biomarkers from Automated Transcription of Spoken Language
N. Tavabi, D. Stück, A. Signorini, C. Karjadi, T. Al Hanai, M. Sandoval, C. Lemke, J. Glass, S. Hardy, M. Lavallee, B. Wasserman, T. F. A. Ang, C. M. Nowak, R. Kainkaryam, L. Foschini & Rhoda Au
Cognitive Digital Biomarkers from Automated Transcription of Spoken Language
N. Tavabi, D. Stück, A. Signorini, C. Karjadi, T. Al Hanai, M. Sandoval, C. Lemke, J. Glass, S. Hardy, M. Lavallee, B. Wasserman, T. F. A. Ang, C. M. Nowak, R. Kainkaryam, L. Foschini & Rhoda Au
Cognitive Digital Biomarkers from Automated Transcription of Spoken Language
Evidation research reveals that the use of voice-based digital biomarkers might be a valuable tool in detecting and differentiating mild cognitive impairment and dementia
N. Tavabi, D. Stück, A. Signorini, C. Karjadi, T. Al Hanai, M. Sandoval, C. Lemke, J. Glass, S. Hardy, M. Lavallee, B. Wasserman, T. F. A. Ang, C. M. Nowak, R. Kainkaryam, L. Foschini & Rhoda Au
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