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Study of Alzheimer’s disease brain impairment and methods for its early diagnosis: a comprehensive survey

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Abstract

Alzheimer’s disease (AD) is one of the most severe kinds of dementia that affects the elderly population. Since this disease is incurable and the changes in brain sub-regions start decades before the symptoms are observed, early detection becomes more challenging. Discriminating similar brain patterns for AD classification is difficult as minute changes in biomarkers are detected in different neuroimaging modality, also in different image projections. Deep learning models have provided excellent performance in analyzing various neuroimaging and clinical data. In this survey, we performed a comparative analysis of 134 papers published between 2017 and 2022 to get 360° knowledge of the AD kind of problem and everything done to examine and deeply analyze factors causing this. Different pre-processing tools and techniques, various datasets, and brain sub-regions affected mainly by AD have been reviewed. Further deep analysis of various biomarkers, feature extraction techniques, Deep learning and Machine learning architectures has been done for the survey. Summarization of the latest research articles with valuable findings has been represented in multiple tables. A novel approach has been used representing classification of biomarkers, pre-processing techniques and AD detection methods in form of figures and classification of AD on the basis of stages showing difference in accuracies between binary and multi-class in form of table. We finally concluded our paper by addressing some challenges faced during classification and provided recommendations that can be considered for future research in diagnosing various stages of AD.

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  1. MNNIT Allahabad, Prayagraj, India

    Shruti Pallawi & Dushyant Kumar Singh

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Pallawi, S., Singh, D.K. Study of Alzheimer’s disease brain impairment and methods for its early diagnosis: a comprehensive survey. Int J Multimed Info Retr 12, 7 (2023). https://doi.org/10.1007/s13735-023-00271-y

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