Review compares precision detection methods for neurological diseases, indicating a shift toward multimodal integration for improved outcomes.
Global population aging has emerged as a major driver of the growing burden of neurological diseases, highlighting the urgent demand for advances in early diagnosis, prevention, and rehabilitation. These conditions are typically characterized by insidious onset and irreversible progression, yet their clinical management remains critically compromised by substantial diagnostic delays, representing an intractable bottleneck for existing detection technologies. Therefore, the development of precise, early-stage detection technologies is crucial for expanding the therapeutic window and improving long-term clinical outcomes, addressing a critical unmet clinical need. Herein, we review and compare precision detection strategies for neurological diseases, focusing on the types and mechanisms of mainstream biosensing platforms. Based on the classification of detection substrates and signal transduction mechanisms, four major bio-detection branches are analyzed, including liquid, exosomal, imaging, and digital biomarker detection, with representative studies demonstrating detection limits reaching femtomolar concentrations, clinical diagnostic sensitivities exceeding 90%, and classification accuracies comparable to or surpassing conventional imaging modalities. The inherent advantages and limitations of each biosensing technology are also comprehensively discussed. This review underscores that future research on neurological biomarker sensing is trending toward multimodal integration, which enables the construction of more robust early warning and prognostic assessment systems. This work aims to provide valuable theoretical insights for clinical translation of relevant sensing technologies and integrated diagnostic and treatment strategies, thereby facilitating the progress of early intervention and rehabilitation for common neurological diseases.
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Lv et al. (2026) studied this question.
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