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Accidental Falls

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A machine learning approach to identify important variables for distinguishing between fallers and non-fallers in older women.

PloS one
Falls are a significant ongoing public health concern for older adults. At present, few studies have concurrently explored the influence of multiple measures when seeking to determine which variables are most predictive of fall risks. As such, this c...

Better informing everyday fall risk assessment: experimental studies with contemporary technologies.

Lancet (London, England)
BACKGROUND: Age-related mobility issues and frailty are a major public health concern because of an increased risk of falls. Subjective assessment of fall risk in the clinic is limited, failing to account for an individual's habitual activities in th...

Fall prediction in a quiet standing balance test via machine learning: Is it possible?

PloS one
The elderly population is growing rapidly in the world and falls are becoming a big problem for society. Currently, clinical assessments of gait and posture include functional evaluations, objective, and subjective scales. They are considered the gol...

Correlation enhanced distribution adaptation for prediction of fall risk.

Scientific reports
With technological advancements in diagnostic imaging, smart sensing, and wearables, a multitude of heterogeneous sources or modalities are available to proactively monitor the health of the elderly. Due to the increasing risks of falls among older a...

Using machine learning models to predict falls in hospitalised adults.

International journal of medical informatics
BACKGROUND: Identifying patients at high risk of falling is crucial in implementing effective fall prevention programs. While the integration of information systems is becoming more widespread in the healthcare industry, it poses a significant challe...

Effects of Language Differences on Inpatient Fall Detection Using Deep Learning.

Studies in health technology and informatics
This study examined the effects of language differences between Korean and English on the performance of natural language processing in the classification task of identifying inpatient falls from unstructured nursing notes.

The Applications of Artificial Intelligence for Assessing Fall Risk: Systematic Review.

Journal of medical Internet research
BACKGROUND: Falls and their consequences are a serious public health problem worldwide. Each year, 37.3 million falls requiring medical attention occur. Therefore, the analysis of fall risk is of great importance for prevention. Artificial intelligen...

A roadmap to artificial intelligence (AI): Methods for designing and building AI ready data to promote fairness.

Journal of biomedical informatics
OBJECTIVES: We evaluated methods for preparing electronic health record data to reduce bias before applying artificial intelligence (AI).