AI in Early Detection of Alzheimer’s: New Digital Biomarkers and Cognitive Assessment Techniques

The early detection of Alzheimer’s is a crucial challenge in clinical practice, as this neurodegenerative disease begins years before symptoms become evident. In this context, artificial intelligence (AI) has emerged as a powerful tool for identifying digital biomarkers and conducting cognitive assessments that can facilitate early and accurate diagnosis. The integration of AI in neurology is transforming how we approach cognitive impairment, enabling more timely and personalized interventions.

Advances in Biomarkers and Cognitive Assessment

The application of AI in the diagnosis of Alzheimer’s has focused on the use of MRI radiomics and fluid biomarkers to classify and predict disease progression. Studies have shown that the analysis of textures and features in medical imaging can differentiate between Alzheimer’s, mild cognitive impairment (MCI), and normal subjects with high sensitivity and specificity. Additionally, immune-related blood biomarkers are emerging as accessible and low-cost methods for early diagnosis.

The use of machine learning algorithms has allowed for the combination of multiple biomarkers, such as neuroimaging data, neuropsychological tests, and genetic information, to create predictive models that enhance diagnostic accuracy. For instance, the integration of multimodal data has proven effective in detecting amyloid plaques, a key marker in the diagnosis of Alzheimer’s.

Conclusions

The incorporation of AI in the early detection of Alzheimer’s represents a significant advancement in modern neurology. Digital biomarkers and cognitive assessment assisted by AI not only improve diagnostic accuracy but also enable earlier intervention, which is crucial for slowing the progression of cognitive impairment. As we continue to develop and refine these technologies, it is essential to address ethical and data privacy challenges to ensure their effective integration into clinical practice.

References

• [1] MRI Radiomics Classification and Prediction in Alzheimer's Disease and Mild Cognitive Impairment: A Review
• [2] Systematic review: fluid biomarkers and machine learning methods to improve the diagnosis from mild cognitive impairment to Alzheimer's disease
• [3] Towards early diagnosis of Alzheimer's disease: advances in immune-related blood biomarkers and computational approaches
• [4] Diagnostic performance of MRI radiomics for classification of Alzheimer's disease, mild cognitive impairment, and normal subjects: a systematic review and meta-analysis

Created 20/1/2025