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EnLiSense CCM Advances Validation of Real-Time IBD Inflammatory Biomarker Monitoring with Two Recent Peer-Reviewed Longitudinal Studies

DALLAS, February 15, 2024 EnLiSense CCM, a pioneer in non-invasive sweat-sensor technology for real-time health monitoring, is thrilled to announce a groundbreaking advancement in the world of Inflammatory Bowel Disease (IBD) management. Our innovative IBD Aware device offers the first solution for continuous, non-invasive monitoring of IBD through the power of sweat-sensing technology.

United statesAndres hurtado lorenzoShalini prasadRobertp hirtenTranslational researchCrohn colitis foundationCrohn colitis foundation novel technologies initiative awardDepartment headUniversity of texas at dallasNational institute of health awardIcahn school of medicine at mount sinaiInflammatory bowel diseaseIcahn schoolMount sinaiColitis foundationAssessment of sweat

EnLiSense CCM Advances Validation of Real-Time IBD Inflammatory Biomarker Monitoring with Two Recent Peer-Reviewed Longitudinal Studies – IT Business Net

EnLiSense CCM Advances Validation of Real-Time IBD Inflammatory Biomarker Monitoring with Two Recent Peer-Reviewed Longitudinal Studies – IT Business Net
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United statesRobertp hirtenAndres hurtado lorenzoShalini prasadIcahn school of medicine at mount sinaiCrohn colitis foundation novel technologies initiative awardDepartment headUniversity of texas at dallasNational institute of health awardCrohn colitis foundationTranslational researchInflammatory bowel diseaseIcahn schoolMount sinaiColitis foundationAssessment of sweat

Could Wearables Capture Well-Being?

Applying machine learning models, a type of artificial intelligence (AI), to data collected passively from wearable devices can identify a patient's

New yorkUnited statesMicol zweigGirishn nadkamiMayte suarez farinasLaurie keeferMaria suprunSparshdeep kaurRobertp hirtenZahi fayadDennis charneyAnthony bielloMatteo danielletoImaging institute at icahn mount sinaiClinical researchIcahn school of medicine at mount sinai

Could Wearables Capture Well-Being?

Applying machine learning models, a type of artificial intelligence (AI), to data collected passively from wearable devices can identify a patient's

New yorkUnited statesGirishn nadkamiLaurie keeferRobertp hirtenDennis charneyMicol zweigMayte suarez farinasMaria suprunMatteo danielletoZahi fayadSparshdeep kaurAnthony bielloIcahn school of medicine at mount sinaiImaging institute at icahn mount sinaiClinical research

AI-Powered Wearables Could Identify User s Mental Health, Well-Being

Researchers used machine learning to analyze data from wearables and detect the well-being of a user.

United statesNew yorkJace dela cruzMicol zweigZahi fayadLas vegasRobertp hirtenConsumer electronics showWearable devices ltdIcahn school of medicine at mount sinaiTech timesIcahn schoolMount sinaiApple watchGetty imagesWearable devices