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@article{182906,
        author = {Koushik ghosh and Jeet Bandyopadhyay and Subhashis Kumar Chandra},
        title = {ML-Based Early Detection of Alzheimer’s Disease Using MRI and Speech Patterns},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {4027-4029},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182906},
        abstract = {Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that significantly impacts memory, cognition, and behavior. Early detection plays a crucial role in slowing disease progression and improving the quality of life for patients. This paper presents a machine learning (ML)-based approach for early detection of Alzheimer’s disease using magnetic resonance imaging (MRI) and speech pattern analysis. By integrating image-based biomarkers with linguistic features, our system aims to enhance diagnostic accuracy. Experimental results demonstrate that multimodal ML models outperform unimodal ones, highlighting the potential of combining neuroimaging and speech analysis for early AD detection.},
        keywords = {Alzheimer’s Disease, Machine Learning, MRI, Speech Patterns, Multimodal Analysis, Early Diagnosis},
        month = {July},
        }