The COVID-19 pandemic has disrupted many industries, and healthcare is no exception. Digital health solutions deployed globally to facilitate extensive re-organisation of healthcare services and de-centralised care in the first 6 months of COVID-19 are presented with an overview of the road ahead.

It’s no secret that telehealth’s explosion is credited to the advent of the COVID-19 pandemic. What role will telehealth play in care delivery in the post-pandemic future?

A deep-learning system detecting fractures across the musculoskeletal system can help reduce common diagnostic errors and improve clinical outcomes

Gun violence is a major cause of death in the United States, yet the data necessary for informing the gun policy debate is woefully incomplete. Internet search patterns have the potential to serve as a valuable complementary information source to existing approaches.

Growing evidence suggests that consumer wearable and smartphone sensor data are related to symptoms, quality of life, and risk for adverse outcomes in cancer. Larger studies that use sensor data to inform and personalize clinical care are needed.

The rate of disability accumulation varies across multiple sclerosis (MS) patients. Machine learning techniques may offer more powerful means to predict disease course in MS patients.

The demand for digital mental health care is high, even more so since Covid-19. However, proper development and testing according to robust standards takes time, as we can show for the development of a digital psychological intervention for youth with OCD.

RCTs and variance in clinical outcomes and patient preferences