AIM: To develop and validate decision trees using conditional probabilities to identify the predictors of mortality and morbidity deterioration in trauma patients.
AIM: To utilise natural language processing (NLP) to analyse interviews about the impact of COVID-19 in underserved communities and to compare it to traditional thematic analysis in a small subset of interviews.
AIMS: The aim of our study was to formulate and validate a prediction model using machine learning algorithms to forecast the risk of pressure injuries (PIs) in children undergoing living donor liver transplantation (LDLT).
BACKGROUND: Research identified preliminary evidence that artificial intelligence (AI) has emerged as a transformative force in healthcare, revolutionising various aspects of healthcare delivery, from diagnostics to treatment planning. However, integ...
AIMS: This study aimed to explore the correlation between artificial intelligence (AI) literacy, AI anxiety and AI attitudes among paediatric nurses, as well as identify the influencing factors on paediatric nurses' AI attitudes.
AIMS: The aim of the study is to develop a model using a machine learning approach that can effectively identify the quality of home care in communities.
AIMS: Early identification and intervention of the frailty of the elderly will help lighten the burden of social medical care and improve the quality of life of the elderly. Therefore, we used machine learning (ML) algorithm to develop models to pred...