Early diagnosis of Alzheimer’s disease through biomarkers, advanced neuroimaging, and artificial intelligence
Abstract
Background: Alzheimer’s disease is the leading cause of dementia worldwide and represents a growing public health challenge in aging populations. Early diagnosis remains a major clinical difficulty, as neuropathological changes precede the onset of cognitive symptoms by several years. In this context, the development of biological biomarkers, advanced neuroimaging techniques, and artificial intelligence has expanded the possibilities for detecting the disease at preclinical and early clinical stages. Objective: To analyze recent scientific evidence regarding the integrated application of biomarkers, advanced neuroimaging methods, and artificial intelligence in the early diagnosis of Alzheimer’s disease. Methods: This scientific work consists of a descriptive and analytical evaluation of original studies published between 2019 and 2025, identified in the PubMed, SciELO, LILACS, and Scopus databases. Data related to the types of biomarkers, neuroimaging modalities, and artificial intelligence applications used for early identification of Alzheimer’s disease were systematically analyzed. Results: The analyzed studies demonstrated that biomarkers such as beta-amyloid and tau proteins allow the detection of early neuropathological changes with high sensitivity. Advanced neuroimaging techniques, including volumetric magnetic resonance imaging and positron emission tomography, showed effectiveness in identifying early structural and metabolic brain alterations. Artificial intelligence algorithms applied to clinical and imaging data exhibited high accuracy in differentiating normal aging, mild cognitive impairment, and early-stage Alzheimer’s disease. Conclusion: The integration of biomarkers, advanced neuroimaging, and artificial intelligence represents a promising strategy for the early diagnosis of Alzheimer’s disease, with potential to improve clinical decision-making, enable earlier interventions, and contribute to advances in cognitive and aging neurology.