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Long-term data from smartwatches can help estimate clinical blood test results

Long-term data from smartwatches can help estimate clinical blood test results
Smartwatches and other wearable devices may be used to sense illness, dehydration and even changes to the red blood cell count, according to biomedical engineers and genomics researchers at Duke University and the Stanford University School of Medicine.
The researchers say that, with the help of machine learning, wearable device data on heart rate, body temperature and daily activities may be used to predict health measurements that are typically observed during a clinical blood test. The study appears in
Nature Medicine on May 24, 2021.
During a doctor s office visit, a medical worker usually measures a patient s vital signs, including their height, weight, temperature and blood pressure. Although this information is filed away in a person s long-term health record, it isn t usually used to create a diagnosis. ....

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Study: Wearables devices can predict health measuresments like a blood test

by Michela Kane May 25, 2021 .
DURHAM – Smartwatches and other wearable devices may be used to sense illness, dehydration and even changes to the red blood cell count, according to biomedical engineers and genomics researchers at Duke University and the Stanford University School of Medicine.
The researchers say that, with the help of machine learning, wearable device data on heart rate, body temperature and daily activities may be used to predict health measurements that are typically observed during a clinical blood test. The study appears in Nature Medicine on May 24, 2021.
During a doctor’s office visit, a medical worker usually measures a patient’s vital signs, including their height, weight, temperature and blood pressure. Although this information is filed away in a person’s long-term health record, it isn’t usually used to create a diagnosis. Instead, physicians will order a clinical lab, which tests a patient’s urine or blood, to gather specific ....

Daniel Witt , Scott Delp , Amir Bahmani , Jennifer Hicks , Sophia Miryam Rose , Sophia Miryam , Schussler Fiorenza Rose , Ryan Runge , Michael Snyder , Jessilyn Dunn , Xiao Li , Lukasz Kidzinski , Trevor Hastie , Stanford Translational Research Integrated Database Environment , Career Development Award , Stanford University School Of Medicine , Common Fund Human Microbiome Project , Duke University , Stanford University , National Institutes Of Health Center , Stanford University School , Nature Medicine , Integrative Personal Omics Profiling , Intel Basis , Apple Watch , Fund Human Microbiome Project ,

Data from smartwatches can help predict clinical blood test results

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Credit: Michaela Kane, Duke University
DURHAM, N.C. Smartwatches and other wearable devices may be used to sense illness, dehydration and even changes to the red blood cell count, according to biomedical engineers and genomics researchers at Duke University and the Stanford University School of Medicine.
The researchers say that, with the help of machine learning, wearable device data on heart rate, body temperature and daily activities may be used to predict health measurements that are typically observed during a clinical blood test. The study appears in
Nature Medicine on May 24, 2021.
During a doctor s office visit, a medical worker usually measures a patient s vital signs, including their height, weight, temperature and blood pressure. Although this information is filed away in a person s long-term health record, it isn t usually used to create a diagnosis. Instead, physicians will order a clinical lab, which tests a patient s urine or blood, ....

Daniel Witt , Scott Delp , Amir Bahmani , Jennifer Hicks , Duke Jessilyn Dunn , Sophia Miryam Rose , Sophia Miryam , Schussler Fiorenza Rose , Ryan Runge , Michael Snyder , Jessilyn Dunn , Xiao Li , Lukasz Kidzinski , Trevor Hastie , Stanford Translational Research Integrated Database Environment , Career Development Award , Stanford University School Of Medicine , Common Fund Human Microbiome Project , Duke University , Stanford University , National Institutes Of Health Center , Stanford University School , Nature Medicine , Integrative Personal Omics Profiling , Intel Basis , Apple Watch ,