Time Series Analysis and Forecasting with Automated Machine Learning on a National ICD-10 Database.

ABSTRACT: The application of machine learning (ML) for use in generating insights and making predictions on new records continues to expand within the medical community. Despite this progress to date, the application of time series analysis has remained underexplored due to complexity of the underlying techniques. In this study, we have deployed a novel ML, called automated time series (AutoTS) machine learning, to automate data processing and the application of a multitude of models to assess which best forecasts future values. This rapid experimentation allows for and enables the selection of the most accurate model in order to perform time series predictions. By using the nation-wide ICD-10 (International Classification of Diseases, Tenth Revision) dataset of hospitalized patients of Romania, we

SUBMITTER: Olsavszky V 

PROVIDER: S-EPMC7400312 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature