Machine Learning-Based Pressure Ulcer Prediction in Modular Critical Care Data.

ABSTRACT: Increasingly available open medical and health datasets encourage data-driven research with a promise of improving patient care through knowledge discovery and algorithm development. Among efficient approaches to such high-dimensional problems are a number of machine learning methods, which are applied in this paper to pressure ulcer prediction in modular critical care data. An inherent property of many health-related datasets is a high number of irregularly sampled time-variant and scarcely populated features, often exceeding the number of observations. Although machine learning methods are known to work well under such circumstances, many choices regarding model and data processing exist. In particular, this paper address both theoretical and practical aspects related to the application

SUBMITTER: Sin P 

PROVIDER: S-EPMC9030498 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature