Artificial Intelligence-Based Hospital Malnutrition Screening: Validation of a Novel Machine Learning Model.

ABSTRACT: Despite its morbidity, mortality, and financial burden, in-hospital malnutrition remains underdiagnosed and undertreated. Artificial intelligence (AI) offers a promising clinical informatics solution for identifying malnutrition risk and one that can be coupled with clinician-delivered patient care.The objectives of the study were to evaluate an AI-based hospital malnutrition screening model in a large and diverse inpatient population and to compare it to the currently used clinician-delivered malnutrition screening tool.We studied the performance of a gradient-boosted decision tree model incorporating a large language model (LLM) for feature extraction using the electronic medical record data of 106,449 patients over 3.75 years.The model's area under the receiver operating curve was 0.92

SUBMITTER: Bernstein AM 

PROVIDER: S-EPMC12618146 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature