What question did this study set out to answer?

The aim is to explore how AI and ML can improve neuroimaging for early detection of brain disorders.

April 23, 2026CureusOpen Access

Artificial Intelligence and Machine Learning in Diagnostic Radiology: A Paradigm Shift Toward Predictive Neuroimaging and Early Detection of Brain Disorders

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This review demonstrates AI and ML's impact on improving early detection of brain disorders, suggesting enhanced diagnostic capabilities.

The aim is to explore how AI and ML can improve neuroimaging for early detection of brain disorders.
Synthesis of recent advancements in AI- and ML-driven neuroimaging.
Analysis of various imaging modalities like MRI and CT.
Discussion of applications in brain tumor characterization, neurodegenerative disorders, and more.
AI-driven approaches show improved diagnostic accuracy and efficiency.
Identification of challenges like data heterogeneity and regulatory concerns.
Need for robust multicenter validation and explainable AI models.

Gupta et al. (2026) studied this question.

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