Unsupervised learning and natural language processing highlight research trends in a superbug.

ABSTRACT: Antibiotic-resistance Acinetobacter baumannii is a very important nosocomial pathogen worldwide. Thousands of studies have been conducted about this pathogen. However, there has not been any attempt to use all this information to highlight the research trends concerning this pathogen. Here we use unsupervised learning and natural language processing (NLP), two areas of Artificial Intelligence, to analyse the most extensive database of articles created (5,500+ articles, from 851 different journals, published over 3 decades). K-means clustering found 113 theme clusters and these were defined with representative terms automatically obtained with topic modelling, summarising different research areas. The biggest clusters, all with over 100 articles, are biased toward multidrug resistanc

SUBMITTER: Mendez-Cruz CF 

PROVIDER: S-EPMC10991725 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature