Decoding Wilson disease: a machine learning approach to predict neurological symptoms.

ABSTRACT:

Objectives

Wilson disease (WD) is a rare autosomal recessive disorder caused by a mutation in the ATP7B gene. Neurological symptoms are one of the most common symptoms of WD. This study aims to construct a model that can predict the occurrence of neurological symptoms by combining clinical multidimensional indicators with machine learning methods.

Methods

The study population consisted of WD patients who received treatment at the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine from July 2021 to September 2023 and had a Leipzig score ≥ 4 points. Indicators such as general clinical information, imaging, blood and urine tests, and clinical scale measurements were collected from patients, and machine learning methods were employed to construc

SUBMITTER: Yang Y 

PROVIDER: S-EPMC11223572 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature