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Discovering Composite Lifestyle Biomarkers With Artificial Intelligence From Clinical Studies to Enable Smart eHealth and Digital Therapeutic Services

Sofoklis Kyriazakos, Aristodemos Pnevmatikakis, Alfredo Cesario, Konstantina Kostopoulou, Luca Boldrini, Vincenzo Valentini, Giovanni Scambia

2021Frontiers in Digital Health27 citationsDOIOpen Access PDF

Abstract

Discovery of biomarkers is a continuous activity of the research community in the clinical domain that recently shifted its focus toward digital, non-traditional biomarkers that often use physiological, psychological, social, and environmental data to derive an intermediate biomarker. Such biomarkers, by triggering smart services, can be used in a clinical trial framework and eHealth or digital therapeutic services. In this work, we discuss the APACHE trial for determining the quality of life (QoL) of cervical cancer patients and demonstrate how we are discovering a biomarker for this therapeutic area that predicts significant QoL variations. To this extent, we present how real-world data can unfold a big potential for detecting the cervical cancer QoL biomarker and how it can be used for novel treatments. The presented methodology, derived in APACHE, is introduced by Healthentia eClinical solution, and it is beginning to be used in several clinical studies.

Topics & Concepts

eHealthBiomarkerClinical trialBig dataMedicineComputer scienceQuality of life (healthcare)Data scienceHealth careData miningInternal medicineBiologyNursingBiochemistryEconomic growthEconomicsMachine Learning in HealthcareArtificial Intelligence in HealthcareRadiomics and Machine Learning in Medical Imaging
Discovering Composite Lifestyle Biomarkers With Artificial Intelligence From Clinical Studies to Enable Smart eHealth and Digital Therapeutic Services | Litcius