The adoption of “artificial intelligence (AI) in drug discovery”, where AI is used in the process
of pharmaceutical research and development, is progressing. By using the ability to process …

Background Frailty is a dynamic and complex geriatric condition characterized by multi-
domain declines in physiological, gait and cognitive function. This study examined whether …

Abstract Convolutional Neural Network (CNN) is a prevalent topic in deep learning (DL)
research for their architectural advantages. CNN relies heavily on hyperparameter …

Background This study aimed to identify the most impactful set of intrinsic and extrinsic fall
risk factors and develop a data-driven inpatient fall risk assessment tool (FRAT). Methods …

Falls are a leading cause of unintentional trauma-related deaths worldwide, and a
significant contributor to elderly dependence. To address this, the goal of this project was to …

Background Existing fall risk assessment tools in clinical settings often lack accuracy.
Although an increasing number of fall risk prediction models have been developed for …

Background Predicting physical function upon discharge among hospitalized older adults is
important. This study has aimed to develop a prediction model of physical function upon …

Background: The effectiveness of applying a fall-risk assessment to prevent falls in residents
of long-term care facilities has not been investigated. Methods: This prospective study …

Objective To compare the performance of the diagnostic model for fall risk based on the
short physical performance battery (SPPB) developed using commercial machine learning …

Background Nodular thyroid disease is by far the most common thyroid disease and is
closely associated with the development of thyroid cancer. Coal miners with chronic coal …