Development and preliminary validation of a machine learning system for thyroid dysfunction diagnosis based on routine laboratory tests.

ABSTRACT:

Background

Approximately 2.4 million patients in Japan would benefit from treatment for thyroid disease, including Graves' disease and Hashimoto's disease. However, only 450,000 of them are receiving treatment, and many patients with thyroid dysfunction remain largely overlooked. In this retrospective study, we aimed to develop and conduct preliminary testing on a machine learning method for screening patients with hyperthyroidism and hypothyroidism who would benefit from prompt medical treatment.

Methods

We collected electronic medical records and medical checkup data from four hospitals in Japan. We applied four machine learning algorithms to construct classification models to distinguish patients with hyperthyroidism and hypothyroidism from control subjects using routine

SUBMITTER: Hu M 

PROVIDER: S-EPMC9053267 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature