Trends and methods in intensive care unit (ICU) research using machine learning: latent dirichlet allocation (LDA)-based thematic literature review.

ABSTRACT:

Introduction

The use of machine learning (ML) in intensive care units (ICUs) has led to a large yet fragmented body of literature. It is imperative to conduct a systematic analysis and synthesis of this research to identify methodological trends, clinical applications, and knowledge deficits.

Methods

A systematic literature review was conducted in accordance with the PRISMA guidelines, encompassing 2,507 ICU-focused ML publications from 2019 to 2024. Latent Dirichlet Allocation (LDA), an unsupervised topic modeling approach, was used with n-gram and no-n-gram tokenization strategies. Bayesian optimization approaches were used to increase model coherence and diversity.

Results

The analysis demonstrated a substantial degree of methodological variability, emphasizing the

SUBMITTER: Topaloglu D 

PROVIDER: S-EPMC12308941 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature