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Neurodiagnostic: Advances in diagnostic tools.

December 19, 2025pubmed logopapers

Authors

Dave S,Banerjee J,Banerjee S,Tiwari AK

Affiliations (4)

  • Genetics & Developmental Biology Laboratory, School of Biotechnology & Bioengineering, Institute of Advanced Research, Gandhinagar, Gujarat, India.
  • Molecular Biology Laboratory, School of Biotechnology & Bioengineering, Institute of Advanced Research, Gandhinagar, Gujarat, India.
  • Biochemistry Laboratory, School of Biotechnology & Bioengineering, Institute of Advanced Research, Gandhinagar, Gujarat, India. Electronic address: [email protected].
  • Genetics & Developmental Biology Laboratory, School of Biotechnology & Bioengineering, Institute of Advanced Research, Gandhinagar, Gujarat, India. Electronic address: [email protected].

Abstract

Understanding the pathologies related to neurological issues, viz. Alzheimer's disease (AD), brain tumors, and multiple sclerosis (MS) are complex and still lack effective therapeutics. Management of the global health burden caused by the escalating cases of neurodegenerative diseases urgently requires early and precise diagnosis. While conventional diagnostic tools like X-ray, Computed Tomography (CT), and Electrophysiological Techniques still hold a crucial role in the field of neurodiagnosis, researchers and clinicians are searching for advancements and the development of cutting-edge tools to enhance diagnostic accuracy, early detection, and improved health outcomes. Some later developed tools like PET and fMRI have proven beneficial in diagnosing the structural and functional aspects of neurological pathologies. However, specific and differential diagnosis for different neurodegenerative diseases is critical. We discuss how Omics studies (including proteomics and genomics), Artificial Intelligence (AI), and Machine learning (ML) have further enhanced the advancements in the field of neurodiagnostics. Our chapter highlights the importance of identifying novel blood-based, cerebrospinal fluid (CSF) based biomarkers while giving emphasis to developing non-invasive biomarkers to uplift the field of neurodiagnosis. The chapter concludes that the importance of the development of advanced bioimaging, multi-omics studies, computational studies, and exploring futuristic technologies, including the development of biosensors, can pave the path for next-generation neurodiagnostic techniques.

Topics

Neurodegenerative DiseasesJournal ArticleReview

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