Malnutrition risk assessment using a machine learning-based screening tool: A multicentre retrospective cohort.
Prathamesh ParchureMelanie BesculidesSerena ZhanFu-Yuan ChengPrem TimsinaSatya Narayana CheertiralaIlana KerschSara WilsonRobert FreemanDavid ReichMadhu MazumdarArash KiaPublished in: Journal of human nutrition and dietetics : the official journal of the British Dietetic Association (2024)
MUST-Plus, a machine learning-based screening tool, shows great promise as a malnutrition screening tool for hospitalised patients when used in conjunction with adequate RD staffing and training about the tool. It performed well across multiple measures and settings. Other health systems can use their electronic health record data to develop, test and implement similar machine learning-based processes to improve malnutrition screening and facilitate timely intervention.
Keyphrases
- machine learning
- electronic health record
- big data
- risk assessment
- artificial intelligence
- end stage renal disease
- randomized controlled trial
- newly diagnosed
- chronic kidney disease
- clinical decision support
- peritoneal dialysis
- deep learning
- prognostic factors
- study protocol
- patient reported outcomes
- heavy metals
- community acquired pneumonia