Background Research on technologies based on artificial intelligence in healthcare has
increased during the last decade, with applications showing great potential in assisting and …

Artificial Intelligence (AI) has transformed how we live and how we think, and it will change
how we practice medicine. With multimodal big data, we can develop large medical models …

Aim To present an overview of how artificial intelligence has been used to improve clinical
nursing care. Background Artificial intelligence has been reshaping the healthcare industry …

Pressure Injuries (PI) are one of the most common health conditions in the United States.
Most acute or long-term care patients are at risk of developing PI. Machine Learning (ML) …

Significance: As the number of hard-to-heal wound cases rises with the aging of the
population and the spread of chronic diseases, health care professionals struggle to provide …

Pressure injuries are increasing worldwide, and there has been no significant improvement
in preventing them. This study is aimed at reviewing and evaluating the studies related to the …

Objective To determine risk factors for pressure injury in distinct intensive care
subpopulations according to admission type (Medical; Surgical elective; Surgery …

Hospital-Acquired Pressure Injury (HAPI), known as bedsore or decubitus ulcer, is one of the
most common health conditions in the United States. Machine learning has been used to …

Aims and objectives To summarize the use of machine learning (ML) for hospital‐acquired
pressure injury (HAPI) prediction and to systematically assess the performance and …

Despite the fact that machine learning (ML) algorithms to construct predictive models for
pressure injury development are widely reported, the performance of the model remains …