DigiBioMarkers 2018 - 2nd Workshop on Digital Biomarkers (DigiBioMarkers 2018)

A biological marker (biomarker) can be defined by any substance, structure, or process of the body, its actions or products that can influence or predict the incidence of disease, health conditions, effects of treatments, and interventions. Digital biomarkers are the user generated physiological and behavioral measures collected via connected digital devices or wearable and mobile computing systems that can be used to explain, influence or predict the health related outcomes. The digital biomarkers do not include genetic information or data collected through traditional medical instruments. Examples of digital biomarkers include everything from geo-location and physical activity traces through internal physiological processes like vital signs to chemical makeups of skin, blood and other tissues collected by IoT devices, smartphones, wearables or novel digital computational platforms.
A set accurately and reproducibly measurable digital biomarkers can be used to predict various health conditions, outcomes. These can also be used to generate actionable insights. The rich data collected with the built-in sensors and processing units of our smartphones and wearable devices have already shown a lot of promise for passive and continuous measurement of several digital biomarkers which can be used to develop all sorts of new health sensing apps and interventions. However, there are a few major bottlenecks in digital biomarker computation, which include (i) the high level of initial setup cost and difficulty for a long-term data collection from a large population, (ii) the l in our existing smartphones, wearables or other digital tools capturing internal states and processes of the human body, (iii) various confounding factors compromising the accuracy and reproducibility of the digital biomarker, (iv) high cost and intrusiveness. The workshop aims to identify a set of solutions to these problems by bringing in key technological innovations from the areas of mobile computing, machine learning, health sciences and medicine.