Assessing the effectiveness of machine learning and deep learning in differentiating neuroimmunological diseases: a systematic review and meta-analysis.

ABSTRACT:

Objective

The differential diagnosis of neuroimmunological disorders remains a significant challenge in clinical practice, even with advancements in diagnostic techniques. Recently, the use of artificial intelligence (AI) for diagnosing and distinguishing between various neuroimmunological disorders has gained traction. Our objective was to conduct a systematic review and meta-analysis to evaluate the diagnostic performance of Machine Learning (ML) and Deep Learning (DL) techniques in differentiating these disorders. We aimed to identify the most effective approaches, compare their diagnostic outcomes, and offer recommendations for improving their applicability across multiple clinical centers and for future research.

Methods

Following the PRISMA 2020 guidelines, a systemati

SUBMITTER: Petrosian D 

PROVIDER: S-EPMC12832442 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature