International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI for Early Detection of Neurological Diseases: A Comprehensive Review |
|---|---|
| ABSTRACT | Neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and Huntington's disease pose considerable global health challenges, marked by progressive neuronal degeneration and functional deterioration. Conventional diagnostic methods frequently detect these conditions only subsequent to significant and irreversible cerebral damage, thereby constraining therapeutic effectiveness. This review investigates the transformative impact of artificial intelligence (AI) in facilitating the earlier identification of neurological disorders through the analysis of multimodal data sources. We combine the latest improvements in machine learning and deep learning for use in neuroimaging, speech patterns, gait analysis, retinal imaging, and clinical data integration. Recent studies show that multimodal AI models consistently do better than single-modality models. For example, they can identify Alzheimer's disease with 92.5% accuracy. New methods like explainable AI, federated learning, and anomaly detection frameworks are helping to solve important problems with model interpretability, data privacy, and finding early prodromal signatures. This review ends by pointing out the current problems and suggesting ways to move forward with putting AI-based diagnostic tools into clinical practice. |
| AUTHOR | PROF. MANJULA P, SINCHANA T, SUHASINI T R, REKHA V N, SANDEEP M, VIKASH K N, SYED SADATH H Assistant Professor, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India UG Students, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India |
| VOLUME | 184 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1405017 |
| pdf/17_AI for Early Detection of Neurological Diseases A Comprehensive Review.pdf | |
| KEYWORDS | |
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