Adverse childhood experiences (ACE) can be retrospectively assessed in adults, ideally before the onset of the diseases under study. There are existing ACE instruments, or attempts to refine these instruments could be undertaken within All of Us.
We will use non-invasive wearable monitoring sensors, similar to a band-aid on the wrist, that measure arterial wave forms at the radial artery in the wrist, providing information on the elasticity and function of cardiovascular system. The information will be uploaded to smartphones and correlated with age and known cardiovascular risk factors, allowing to develop computational models to rapidly identify people at risk... more »
We will reach out to the public to upload eye images using smartphones and evaluate them, creating a large corpus of human eye images. A convolutional neural network will be trained to diagnose eye diseases, and then used to remotely provide human-level prescreening and diagnosis to patients, for easy and early detection and treatment. Few studies started building AI systems but the available images are insufficient.... more »