Background Artificial intelligence (AI) holds the promise of supporting nurses' clinical
decision-making in complex care situations or conducting tasks that are remote from direct …

Background Wearable devices hold great promise, particularly for data generation for cutting-
edge health research, and their demand has risen substantially in recent years. However …

The role of physicians has always been to synthesize the data available to them to identify
diagnostic patterns that guide treatment and follow response. Today, increasingly …

Falls are a significant problem for persons with multiple sclerosis (PwMS). Yet fall prevention
interventions are not often prescribed until after a fall has been reported to a healthcare …

Background Short-term fall prediction models that use electronic health records (EHRs) may
enable the implementation of dynamic care practices that specifically address changes in …

Falls are among the most common cause of decreased mobility and independence in older
adults and rank as one of the most severe public health problems with frequent fatal …

Introduction Monitoring systems at home are critical in the event of a fall, and can range from
standalone fall detection devices to activity recognition devices that aim to identify behaviors …

Sensor-based fall risk assessment (SFRA) utilizes wearable sensors for monitoring
individuals' motions in fall risk assessment tasks. Previous SFRA reviews recommend …

Background Falling is common in people with multiple sclerosis (MS) but tends to be under-
ascertained and under-treated. Objective To evaluate fall risk in people with MS. Methods …

The objective was to propose a fall-classification framework for patients undergoing total
knee replacement (TKR). In addition, we reinforced the available evidence on fall incidence …