Técnicas no invasivas para la detección temprana de la enfermedad de Alzheimer: una revisión

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder primarily affecting older adults, characterized by memory loss, cognitive decline, and behavioral changes. As one of the leading causes of dementia worldwide, the prevalence of AD has been rising due to the aging global population, presenting significant public health, social, and economic challenges. While no cure exists, early detection plays a crucial role in slowing disease progression and improving patient outcomes. Recent advancements in computer vision have shown great promise in medical contexts, particularly for early Alzheimer's diagnosis. Non-invasive techniques leveraging AI, such as speech analysis and gait monitoring, offer innovative approaches to detecting subtle cognitive and physical changes associated with the early stages of Alzheimer's. This work reviews the application of computer vision in medical imaging for AD diagnosis and explores emerging and non-invasive technologies that could enhance diagnostic accuracy, reduce reliance on invasive procedures, and support earlier interventions.