Predicting Asthma Exacerbations Using Machine Learning Models.

ABSTRACT:

Introduction

Although clinical, functional, and biomarker data predict asthma exacerbations, newer approaches providing high accuracy of prognosis are needed for real-world decision-making in asthma. Machine learning (ML) leverages mathematical and statistical methods to detect patterns for future disease events across large datasets from electronic health records (EHR). This study conducted training and fine-tuning of ML algorithms for the real-world prediction of asthma exacerbations in patients with physician-diagnosed asthma.

Methods

Adults with ≥ 2 ICD9/10 asthma codes within 1 year and at least 30 days apart were identified from the Optum Panther EHR database between 2016 and 2023. An emergency department (ED), urgent care, or inpatient visit for asthma, while on syste

SUBMITTER: Turcatel G 

PROVIDER: S-EPMC11782383 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature